Abstract
Autoreactive CD8^+ T cells targeting neurons are the principal suspects
in autoimmune encephalitis (AIE), but supporting data is still lacking.
Here we identify neuron-reactive CD8^+ T cells in a cohort of six
healthy donors and one patient with anti-Ri encephalitis (Ri-AIE) by
querying natural antigen presentation of neurons that are derived from
human induced pluripotent stem cells. Single-cell RNA sequencing of ex
vivo CD8^+ T cells in an extended cohort of seven Ri-AIE patients and
three aged-matched controls further reveal that these neuron-reactive
CD8^+ T cells correspond to cytotoxic KIR^+CD8^+ regulatory T cells.
Intriguingly, KIR^+CD8^+ T cells from most Ri-AIE patients have reduced
expression of KIR and the key regulatory transcription factor, Helios,
encoded by the IKZF2 gene; by contrast, these cells show activated TCR
signaling and increased TNF and IFNG gene expression. Importantly,
Ri-AIE-derived KIR^+CD8^+ T cells from blood also express higher levels
of TOX, a gene associated with encephalitogenic potential, and is
expressed in cytotoxic CD8^+ T cells in the brain lesions of one Ri-AIE
patient. Altogether, our data hints that dysregulated activity of
neuron-reactive cytotoxic KIR^+CD8^+ T cells may contribute to Ri-AIE
pathogenesis.
Subject terms: Neuroimmunology, Autoimmune diseases, Gene regulation in
immune cells, CD8-positive T cells
__________________________________________________________________
Autoimmune encephalitis (AIE) may involve neuron-specific cytotoxic T
cells, but evidence is still lacking. Here the authors use induced
pluripotent stem cells from patients with AIE and single cell
RNA-sequencing of ex vivo CD8 T cells to find neuron-specific,
KIR^+CD8^+ T cells with altered transcriptome that potentially
contribute to AIE etiology.
Introduction
Autoimmune encephalitis (AIE) is a heterogenous group of neurological
syndromes characterized by the presence of autoreactive antibodies
targeting neuronal or glial antigens located in the intracellular
compartment or cellular surface^[70]1. In the former case, it is
suspected that, following an immunogenic event such as tumor
development or infection, autoreactive CD8^+ T cells from the periphery
drive disease pathology through the infiltration of the central nervous
system (CNS) and direct recognition of antigens presented by HLA class
I molecules on neurons^[71]2–[72]4. In this context, tumor- or
pathogen-related antigens would activate peripheral CD8^+ T cells and
neurological damage would arise without the necessity of an initial
CNS-related insult^[73]3. As compared to AIE with surface-targeting
antibodies, AIE with intracellular-targeting antibodies shows a higher
brain infiltration of cytotoxic CD8^+ T cells with a higher number of
granzyme B^+ T cells affixed to neurons and a correlation of those
CD8^+ T cells with neuronal damage^[74]2,[75]3,[76]5. Oligoclonal CD8^+
T cell expansion has been reported in the blood, brain tissue, and
dorsal root ganglia of patients with AIE^[77]6–[78]8. Similarly, other
paradigmatic neuroimmunological diseases such as Rasmussen encephalitis
(RE) and Susac syndrome (SuS) also display oligoclonal CD8^+ T cell
expansion, thus suggesting a common CD8^+ T cell-driven pathology in
these disorders^[79]9,[80]10.
While the phenotype and T cell repertoire of CD8^+ T cells in RE and
SuS have been vastly studied^[81]9,[82]10, similar studies with
in-depth CD8^+ T cell assessment are mostly lacking for AIE. Despite
many efforts, neuron-reactive CD8^+ T cells have not been consistently
found in AIE patients. Circulating cdr2 (Yo)- and HuD-specific CD8^+ T
cells have been identified in paraneoplastic cerebellar degeneration
and anti-Hu encephalitis patients, respectively^[83]6,[84]11–[85]13.
Yet, other groups have also contested evidence for circulating CD8^+ T
cells against both these antigens^[86]14–[87]16.
In summary, evidence regarding the phenotype of allegedly autoreactive
pathogenic CD8^+ T cells in AIE is scarce and identification of
neuron-reactive CD8^+ T cells is still elusive^[88]6–[89]10. One of the
reasons for the limited results published so far is that previous
studies were restricted to testing CD8^+ T cell reactivity against the
same antigens as the ones recognized by antibodies. Yet, there is no
evidence that both the humoral and the cellular immune response should
necessarily be directed against the very same protein. Additionally,
whilst certain authors assessed a broad range of candidate epitopes by
generating peptide libraries and transfecting antigen-presenting cells
(APCs) with HLA molecules, these methods have never been applied to
studying AIE and also have limitations^[90]17. In particular, these
techniques require the pre-selection of a restricted number of antigens
and HLA alleles. Furthermore, these techniques, coupled with subsequent
conventional readouts, usually are not able to detect CD8^+ T cell
clonotypes that are present at a frequency lower than 0.01%^[91]18.
Given the state of the art, we believe that there is a need to develop
novel methodologies to address the limitations of current techniques.
First, the search for neuron-reactive CD8^+ T cells should be conducted
in a fully human and, ideally, autologous setting. Second, the
experimental setup must include the largest possible range of neuronal
antigens to develop an unbiased approach. Third, this approach should
be able to take into account protein isoforms or post-translational
modifications that can affect antigen recognition by CD8^+ T
cells^[92]19,[93]20.
Here, to fulfill all these criteria, we develop a method to assess
CD8^+ T cell activation against a broad repertoire of antigens
naturally produced and presented by autologous hiPSC-derived neurons.
Then, given the strong rationale for the role of autoreactive CD8^+ T
cells in AIE, we explore the presence of neuron-reactive CD8^+ T cells
in a total of seven patients with Ri-AIE. We identify neuron-reactive
CD8^+ T cells in both control and diseased donors and uncover key
dysregulated pathways specifically in CD8^+ T cells from Ri-AIE
patients. Overall, this study provides evidence for the implication of
dysregulated autoreactive cytotoxic CD8^+ T cells in Ri-AIE and, most
importantly, it presents a novel methodology that can be applied to
other autoimmune diseases.
Results
To assess the global CD8^+ T cell response against neurons, we resort
to the use of autologous human induced pluripotent stem cell
(hiPSC)-derived neurons^[94]21,[95]22 as APCs. First, to validate this
approach, we generated hiPSCs from six healthy donors (HDs) and
differentiated these hiPSCs into neurons. We then assessed their
capacity to trigger antigen-dependent CD8^+ T cell activation. Upon
stimulation with IFNγ and TNFα, we found that hiPSC-derived neurons
display HLA class I molecules at their surface (Fig. [96]1a, b,
Supplementary Fig. [97]1). We next assessed the capacity of
hiPSC-derived neurons to activate CD8^+ T cells in an antigen-dependent
manner. For this, we performed an overnight stimulation of ex vivo
CD8^+ T cells with autologous neurons pulsed with CD8^+ T
cell-restricted viral peptide pools (see Supplementary Tables [98]1 and
[99]2). In this assay, we were able to elicit an IFNγ secretion by
CD8^+ T cells that correlates with the secretion induced in total
peripheral blood mononuclear cells (PBMCs) during a standard IFNγ
ELISpot assay, demonstrating the capacity of neurons to trigger
antigen-dependent activation of CD8^+ T cells (Fig. [100]1c).
Fig. 1. Human iPSC-derived neurons trigger antigen-dependent CD8^+ T cell
activation.
[101]Fig. 1
[102]Open in a new tab
a Representative fluorescence microscopy images of hiPSC-derived
neurons from HD6, immunostained for NF-200 (magenta), HLA-ABC (yellow)
and DAPI (blue), untreated (left panels, control) or treated with IFNγ
and TNFα for 48 h (right panels, IFNγ + TNFα). Bar represents 100 μm. b
Flow cytometry analysis of HLA class I expression (anti-HLA-ABC
antibody (clone W6/32)) of hiPSC-derived neurons from 6 healthy donors
(HD1-HD6), untreated (control) or treated with IFNγ and TNFα for 48 h
(two-sided Wilcoxon test, p value = 0.0156). n = 6 biological
replicates (i.e., donors), in one experiment. c Correlation of the
number of spot-forming units (SFU)/million PBMCs in an IFNγ ELISpot
assay (y-axis) versus the percentage of IFNγ^+CD8^+ T cells as measured
by IFNγ secretion assay (x-axis). In both assays, PBMC (ELISpot) or
neurons (IFNγ secretion assay) were pulsed overnight with a pool of
CD8^+ T cell-restricted immunodominant viral epitopes from EBV, CMV and
VZV. Correlations were assessed by running a two-sided Pearson
correlation test. n = 9 biological replicates (3 peptide pools per 3
donors), in one experiment.
As neuron-reactive CD8^+ T cell clonotypes are also present in healthy
donors^[103]23, we initially sought to demonstrate the feasibility of
our method in a cohort of HDs. To identify neuron-reactive CD8^+ T cell
clonotypes, we developed a coculture system between PBMCs and
autologous hiPSC-derived neurons and monitored CD8^+ T cell
proliferation after in vitro autologous coculture. We assessed the
TCR-β chain repertoire of CD8^+ T cells after 14 days of culture and
compared it to the ex vivo CD8^+ T cell repertoire (Fig. [104]2a). We
first performed this assay using PBMCs from 6 HDs and performed
conventional TCR-β chain repertoire metric assessments (Shannon
entropy: a measure of TCR repertoire diversity; clonality: a measure of
evenness of TCR chain distribution). We observed a global yet
non-significant decrease in the clonality (average of 0.3 ex vivo vs
0.25 at 14 days, p value: 0.25) and of the Shannon entropy (average of
11.095 ex vivo vs 9.96 at 14 days, p value: 0.21) in the TCR repertoire
after the culture (Fig. [105]2b).
Fig. 2. Human iPSC-derived neurons trigger the expansion of rare
neuron-reactive CD8^+ T cell clonotypes in healthy donors.
[106]Fig. 2
[107]Open in a new tab
a Schematic representation of the experimental workflow for the
identification of neuron-reactive CD8^+ T cell clonotypes. First, a
coculture of PBMCs with autologous neurons is performed for 14 days.
Second, TCR-β chain repertoires at day 14 of coculture are compared to
ex vivo TCR-β repertoires to identify expanded TCR-β chains. Third,
paired TCR-α chains of expanded clonotypes are identified by scTCRseq,
and both TCR-α and TCR-β chains are co-transfected into NFAT-luciferase
reporter Jurkat CD8^+ T cells, which are then cultured overnight with
neurons. Luminescence values are then measured on a multimode
microplate reader (see methods). Created in BioRender. Perriot, S.
(2025) [108]https://BioRender.com/duayzpo. b TCR-β chain repertoire
clonality (top) and Shannon entropy (bottom) of CD8^+ T cells ex vivo
and after 14 days of neuron-PBMC coculture for all 6 HDs (two-sided
Wilcoxon tests). n = 6 biological replicates (i.e., donors), performed
once per donor across 2 independent experiments. c TCR-β chain
repertoire analysis of the CD8^+ T cells from 6 HD ex vivo and after
14 days of coculture. Each slice represents a unique TCR-β sequence.
Slice size represents the frequency of each sequence in comparison with
the total TCR-β chain sequences. Colored slices represent TCR-β chains
that underwent a 9-fold expansion as compared to ex vivo frequencies,
and that constitute >0.5% of total TCR-β after 14 days of coculture.
The asterisk indicates the only TCR-β representing more than 0.5% ex
vivo (HD1). The value at the center of each pie chart represents the
clonality of each TCR-β repertoire. All TCR-β sequences <1:1000 are
grouped into one slice (black and grey patterned slice). n = 6
biological replicates (i.e., donors), performed once per donor across 2
independent experiments. d Luminescence values of TCR-transfected
NFAT-luciferase Jurkat cells after overnight culture with autologous
neurons. Overnight culture was performed with Jurkat cells bearing TCRs
that were identified as expanded in HD4 (blue) or prevalent TCR-β
chains at day 14 that were non-expanded (grey). All luminescence values
are adjusted to the background signal emitted by each respective TCR.
For each clonotype, experimental conditions include neurons treated and
non-treated with IFNγ + TNFα (thus HLA class I positive and negative,
respectively) or with the addition of a blocking anti-HLA-ABC antibody
(clone W6/32). Differences between resting vs stimulated conditions
were assessed by a Kruskal–Wallis test: ns, not significant;
**p < 0.01; ***p < 0.001. Expanded clonotypes, +IFNγ/TNFα vs
+IFNγ/TNFα/anti-HLA: adj. p value = 0.0002. Expanded clonotypes,
+IFNγ/TNFα vs -IFNγ/TNFα: adj. p value = 0.0021. n = 6 biological
replicates (i.e., unique TCRs), this experiment was performed once.
Data are presented as mean values ± SEM.
We then analyzed the TCR β-chain sequences to identify reactive CD8^+ T
cell clonotypes that would have been expanded upon coculture with
autologous neurons. We considered a clonotype to be expanded in vitro
if the TCR-β chain frequency presented with a ≥9-fold expansion as
compared to ex vivo samples. After coculture, we observed several TCR-β
chains whose frequencies were significantly increased after 14 days of
culture (Fig. [109]2c). Focusing on TCR-β chains representing >0.5% of
total repertoire at day 14, we could highlight a specific enrichment
with a mean of 5.33 clonotypes per donor (range 1–12), representing
from 0.5% to 7.2% of the total repertoire (Fig. [110]2c). Only one
TCR-β chain was found at an ex vivo frequency >0.01% (HD1—TCR-β chain:
0.13%, asterisk in Fig. [111]2c). To ensure that these expanded
clonotypes recognize neurons, we restimulated CD8^+ T cells with
autologous neurons and sorted IFNγ^+CD8^+ T cells in 96-well plates at
one cell per well. We next amplified the mRNA sequences encoding the
TCR-α and TCR-β chains in each well separately in order to reconstruct
the TCRs of these cells. Using this approach, we selected 12 TCRs from
HD4, which we cloned into Jurkat cells to assess their reactivity. We
selected 6 clonotypes that we thought would recognize neurons based on
their expansion kinetics in vitro, while the 6 other clonotypes were
classified as non-expanded (did not display an exponential increase
between day 7 and day 14 of coculture, Supplementary Table [112]3).
When cultured with autologous neurons, 6/6 TCRs extracted from
neuron-expanded CD8^+ T cells displayed a specific activation. The
addition of an anti-HLA class I blocking antibody, preventing the
TCR-HLA interaction, specifically abrogated this activation. Similarly,
neurons that were not stimulated with IFNγ and TNFα, thus not
presenting antigens through HLA class I molecules, did not elicit any
TCR activation (Fig. [113]2d). Conversely, TCRs cloned from
non-expanded (i.e., fold-increase <2 compared to ex vivo) CD8^+ T cells
at day 14 did not activate in contact with autologous neurons, thus
demonstrating that our technique efficiently expands neuron-reactive
CD8^+ T cells (Fig. [114]2d).
Next, we looked for the presence of neuron-reactive CD8^+ T cells in a
patient suffering from anti-Ri-AIE (Ri01), in which the autoantibodies
target an intracellular antigen. As described for HDs, we generated
hiPSC-derived neurons that upregulated HLA class I molecules upon IFNγ
and TNFα exposure (43.4 fold change as measured by flow cytometry,
Fig. [115]3a for fluorescence microscopy observations). We next
performed our autologous PBMC-neuron coculture assay to assess whether
we could identify neuron-reactive CD8^+ T cells in this patient. In
sharp contrast with HDs (Fig. [116]2b), CD8^+ T cells from the Ri01
patient revealed the monoclonal expansion of one TCR-β chain,
representing 58.81% of the total repertoire at day 14 (vs 6.47% ex
vivo, Fig. [117]3b). Interestingly, the TCR-β chain repertoire
clonality increased from 0.34 ex vivo to 0.6 (1.76 fold increase) after
coculture (Fig. [118]3b) while HD clonality displayed a decrease from a
mean of 0.3 ex vivo to 0.25 (0.85 fold change) (Fig. [119]2b). To
verify if the expanded TCR β-chain belonged to a TCR reactive for
neurons, and since one concomitant TCR-α chain was also expanded at day
14, we cloned the paired TCR α- and β-chains into Jurkat cells and
assessed their activation. Upon overnight coculture with neurons from
Ri01, we could validate that this TCR recognizes neurons and that the
antigen-dependent activation was blocked by the addition of an anti-HLA
class I antibody (Fig. [120]3c). Additionally, the most prevalent yet
non-expanded clonotype was used as a control and did not react against
neurons (Fig. [121]3c).
Fig. 3. Autologous hiPSC-derived neuron-reactive CD8^+ T cells present with
an important clonal expansion in a patient with Ri-AIE.
[122]Fig. 3
[123]Open in a new tab
a Representative fluorescence microscopy images of hiPSC-derived
neurons from Ri01 immunostained for NF-200 (magenta), HLA-ABC (yellow)
and DAPI (blue), untreated (left panels, control) or treated with IFNγ
and TNFα (right panels, IFNγ + TNFα) for 48 h. Bar represents 100 μm. b
TCR-β chain repertoire analysis of the CD8^+ T cells from Ri01 ex vivo
(left) and after 14 days (right) of coculture with neurons. Each slice
represents a unique TCR-β sequence, and the size of the slice
represents the frequency of each sequence in comparison with total
TCR-β sequences. Strongly expanded clone at D14 is displayed in dark
orange with a prevalent yet non-expanded (i.e., control) clonotype in
light orange. The value at the center of each pie chart represents the
clonality of each TCR-β chain repertoire. All TCR-β sequences <1:1000
are grouped into one slice (black and grey patterned slice). n = 1. c
Luminescence values of TCR-transfected NFAT-luciferase Jurkat cells
after overnight culture with neurons from Ri01. Experimental conditions
include a transactivating anti-CD3/CD28 antibody without neurons,
neurons treated or non-treated with IFNγ and TNFα or with the addition
of a blocking anti-HLA-ABC antibody (clone W6/32). Jurkat cells were
either transfected with the strongly expanded TCR identified in b)
(dark orange) or with the most frequent yet non-expanded TCR at day 14
(light orange). Data are presented as mean values ± SEM. The expanded
clonotype has been validated in n = 3 independent experiments.
Next, to further investigate the phenotype of CD8^+ T cells in Ri-AIE,
we performed single-cell RNA sequencing (scRNAseq) on sorted ex vivo
circulating CD8^+ T cells from seven patients with Ri-AIE (including
Ri01 patient for whom we had found the neuron-reactive CD8^+ T cell
clonotype) as well as three sex- and age-matched donors without an
autoimmune disease (AgD) (Fig. [124]4a, Supplementary Tables [125]4 and
[126]5). Unsupervised clustering with all samples combined highlighted
16 different clusters (Fig. [127]4b) with different CD8^+ T cell
populations according to conventional phenotyping markers^[128]24.
Clusters 3–5 were enriched in naive CD8^+ T cells; clusters 0, 1, 13,
and 14 in effector cytotoxic CD8^+ T cells; clusters 6 and 12 in
activated CD8^+ T cells; and clusters 2, 10, and 15 in memory CD8^+ T
cells (Supplementary Fig. [129]2). We observed a similar distribution
of all samples across all clusters (Supplementary Fig. [130]3a, b).
Furthermore, when comparing cluster repartition between AgD and Ri-AIE
groups, we did not observe significant differences in CD8^+ T cell
frequency per cluster, except for cluster 6, which was enriched in
Ri-AIE patients (Supplementary Fig. [131]3c). Focusing on
neuron-reactive CD8^+ T cells from Ri01 patient (Fig. [132]3), we
noticed that 93.48% of the cells from this clonotype were present in
cluster 1, the remaining minority of cells being localized in clusters
2, 8, 14, and 3 (Fig. [133]4c).
Fig. 4. Neuron-reactive KIR^+CD8^+ T cells are a common feature in aged
donors and Ri-AIE patients.
[134]Fig. 4
[135]Open in a new tab
a Schematic representation of the experimental workflow for the
identification of the neuron-reactive CD8^+ T cell clonotypes and
associated phenotypes. Single-cell RNA sequencing (scRNAseq) was
performed on ex vivo circulating CD8^+ T cells from seven patients with
Ri-AIE (including Ri01) as well as three sex-and age-matched donors
without an autoimmune disease (AgDs). Data were analyzed altogether by
unsupervised clustering. Both neuron-reactivity (via TCR-transfection
into NFAT-luciferase reporter Jurkat cells) and phenotype of selected
clonotypes were further investigated in Ri-AIE vs AgD. Created in
BioRender. Perriot, S. (2025) [136]https://BioRender.com/nhxjm7k. b
UMAP displaying unsupervised clustering of ex vivo CD8^+ T cells from
three AgDs and seven Ri-AIE patients assessed by scRNAseq, resulting in
16 different clusters. c Highlighting of cluster 1 (green) and CD8^+ T
cells presenting with the same TCR-β chain CDR3 amino acid sequence as
the strongly expanded neuron-reactive clonotype from Ri01 (red). The
pie chart on the top right highlights the cluster repartition of this
clonotype, with each cluster represented in a different color and
slices representing the percentage of cells belonging to each cluster
from (b). d Pie charts representing the distribution of clonotypes
(left) and cells (right) from AgDs (top) and Ri-AIE patients (bottom)
present in cluster 1. The proportion of CD8^+ T cells with one unique
TCR is displayed in dark grey and those with ≥2 identical TCR in light
grey (i.e., expanded ex vivo). Clonotypes were selected and tested for
neuron-reactivity if they presented with the following criteria: (1) a
clonotype with ≥10 CD8^+ T cells in cluster 1; (2) >60% of CD8^+ T
cells from this clonotype present in cluster 1. From CD8^+ T cells
fulfilling these criteria, we selected 27 from AgD (blue slice) and 21
from Ri-AIE (orange slice). e Dot plot representing luminescence values
of TCR-transfected NFAT-luciferase Jurkat cells from AgD (blue) or
Ri-AIE (orange) after overnight culture with HLA-enhanced neurons
(matched for HLA haplotype). Horizontal dotted line represents
positivity threshold established at a luminescence value of 5000
(neuron-reactive CD8^+ T cell clonotypes are highlighted in darker
shades of blue (AgD) or orange (Ri-AIE)). For both groups, a control
condition with a blocking anti-HLA-ABC was included to ensure that the
activation of Jurkat cells was TCR-mediated (two-sided Wilcoxon test,
AgD p value = 0.001, Ri AIE p value = 0.0003 among neuron-reactive
CD8^+ T cells). n = 27 for AgD and n = 21 for Ri-AIE, neuron-reactive
clonotypes were validated once per TCR across two independent
experiments. Data are presented as mean values ± SEM. f Bar plots
summarizing the proportion of neuron-reactive clones (blue) vs
non-reactive clones (light blue) among AgDs (left) and Ri-AIE patients
(orange vs light orange, right). g Heatmap displaying differentially
expressed genes among all 16 clusters (x-axis). Genes displayed on
y-axis are classified into functional categories conventionally used to
classify CD8^+ T cell phenotype. Upregulated genes are displayed in red
with downregulated genes in blue.
Given that almost all these identified neuron-reactive CD8^+ T cells
were gathered in cluster 1, we turned to this unique cluster to further
look for neuron-reactive CD8^+ T cells in the remaining six Ri-AIE
patients and three AgDs. Interestingly, within this cluster, we found
no difference in the TCR-β chain repertoire metrics (clonality and
Shannon entropy) between the AgD and Ri-AIE groups (Supplementary
Fig. [137]4a). Globally, cluster 1 was composed of 11,598 cells from
1184 individual clonotypes. We found 488 individual clonotypes from
5014 cells in all AgDs (average of 162.7 clonotypes/donor) versus 696
clonotypes from 6584 cells in Ri-AIE (average of 99.4 clonotypes/donor,
Fig. [138]4d). Among them, 39.5% and 45.2% of these clonotypes were
found expanded ex vivo (i.e. ≥2 cell per clonotype) in AgDs and Ri-AIE
respectively, without significant differences between groups
(Fig. [139]4d). Of note, expanded clonotypes represented 94.1% of all
cells from cluster 1, congruent with an enrichment in effector CD8^+ T
cells. To determine whether any of these ex vivo expanded clonotypes
recognized neurons, we selected within cluster 1 several clonotypes per
donor among those that displayed the strongest expansion. Clonotypes
were selected according to the following criteria: (1) >10 CD8^+ T
cells in cluster 1; and (2) >60% of cells from this clonotype present
in cluster 1. We selected a total of 48 clonotypes, 27 from AgDs (49.1%
of all expanded CD8^+ T cells ex vivo in cluster 1 from AgDs) and 21
from Ri-AIE (23.7% of all expanded CD8^+ T cells ex vivo in cluster 1
from Ri-AIE), fulfilling the above definition (Fig. [140]4d). We
individually cloned these 48 TCRs into Jurkat cells (Supplementary
Data [141]1) and assessed the luminescence induced by TCR activation
after an overnight culture with partially HLA-matched hiPSC-derived
neurons. On average, 4.66/6 HLA-class I alleles were matched for AgDs
and 5.42/6 for Ri-AIE patients, with an average of 9 clonotypes/donor
tested for AgDs and 3 clonotypes/donor for Ri-AIE (Supplementary
Table [142]6). We observed an HLA-mediated TCR activation in 40.7% of
AgD clonotypes and 42.9% of Ri-AIE clonotypes (no statistical
difference) that was completely abolished in presence of a blocking
anti-HLA-ABC antibody (Fig. [143]4e). We then assessed the ex vivo
frequency of these neuron-reactive CD8^+ T cell clonotypes in AgD and
Ri-AIE groups and observed no significant difference (Supplementary
Fig. [144]4b). To investigate if these TCRs cross-reacted with
peripheral antigens, we cocultured TCR-expressing Jurkat cells with
PBMCs from the same donors as for the hiPSC-derived neurons. We found
that 85% of the neuron-reactive TCRs also activated upon culture with
PBMCs, but with less intensity than neurons (Supplementary
Fig. [145]4c). Altogether, these data demonstrate that autoreactive
CD8^+ T cells recognizing neurons are a common feature of the aged
repertoire and not exclusive to Ri-AIE patients.
We next dived into the characterization of these neuron-reactive
clonotypes to start unveiling the functionality of CD8^+ T cells from
cluster 1. Among the most discriminant genes defining this cluster, we
found that killer cell immunoglobulin-like receptors (KIR), including
KIR2DL1, KIR2DL3, KIR2DL4, KIR3DL1, KIR3DL2 and KIR3DL3, ranked among
the top 10 most upregulated genes along with the transcription factor
IKZF2 (Helios), and the killer cell lectin like receptors (KLR) KLRC2
(NKG2C) and KLRC3 (NKG2E) (Supplementary Data [146]2). These data
indicate that the CD8^+ T cells from cluster 1 are enriched in
KIR^+CD8^+ Treg cells. We further characterized the phenotype of these
cells by assessing the expression of activation markers, costimulatory
receptors, cytotoxic markers, immune regulation, checkpoint inhibitors,
KIRs and a set of transcription factors (Fig. [147]4g). Overall, the
KIR^+CD8^+ Treg cells signature could be fully validated with cells
from cluster 1 highly expressing not only the afore mentioned KIR
family genes and the transcription factor IKZF2 (Helios) but also
additional transcription factors such as TOX and EOMES, an effector
cytotoxic signature (PRF1, GZMA, GZMB, IFNG, TNF) as well as certain
checkpoint inhibitors (CD160, CD244, TIGIT), concordant with TOX
expression (Fig. [148]4g).
Interestingly, KIR^+CD8^+ Treg cells are known to be increased in
aging, infection, cancer and autoimmunity^[149]25–[150]27. Their
primary function seems to be killing autoreactive CD4^+ T cells through
classical cytotoxicity to prevent autoimmunity^[151]25. We thus
hypothesized that neuron-reactive KIR^+CD8^+ Treg cells may display an
altered phenotype in Ri-AIE, which would contribute to the development
of CNS autoimmunity. We thus performed a differential gene expression
analysis at the single cell level, comparing the transcriptomic profile
between neuron-reactive KIR^+CD8^+ Treg cells in cluster 1 from Ri-AIE
patients and AgDs. We found 238 upregulated genes (logFC > 0.5, adj-p
value < 0.05) and 437 downregulated genes (logFC < −0.5, adj-p
value < 0.05; Fig. [152]5a, Supplementary Data [153]3). The top five
most enriched KEGG pathways corresponded to antigen processing and
presentation, Leishmaniasis, rheumatoid arthritis, Th17 cell
differentiation, and human T-cell leukemia virus 1 infection
(Fig. [154]5b). Because these KEGG pathways are associated with
increased T cell activation and cytotoxicity, we selected a large panel
of genes covering important aspects of CD8^+ T cell functions, such as
KIR-related markers, effector functions (cytotoxicity and cytokine
production) as well as TCR activation and TCR inhibition, activation
markers and pro-inflammatory signaling. First, neuron-reactive
KIR^+CD8^+ Treg cells from Ri-AIE patients, as compared to AgDs,
displayed a significant decrease in markers associated with Treg
phenotype, in particular IKZF2 (Helios), genes of the KLR family
(KLRC2, KLRC3, KLRK1) and the inhibitory receptors KIR2DL1 and KIR2DL3.
Receptors from the KIR3DL subfamily tended to decrease as well
(Fig. [155]5c). Interestingly, KIR2DL4, the only activator receptor of
the KIR2DL family, displayed a trend of increase (1.77-fold increase).
As KIRs act by modulating TCR downstream signaling, we sought to assess
if this global downregulation of inhibitory receptors was associated
with TCR activation. Consistent with this decrease of inhibitory
receptors, neuron-reactive KIR^+CD8^+ T cells from Ri-AIE displayed a
strong increase in genes associated with TCR activation (FOS, FOSB,
JUN, JUND, RELB, EGR1, EGR2; Fig. [156]5d) and a global trend to a
decrease in genes active in TCR signaling inhibition, INPP5D (SHIP1)
and CBLB being significantly downregulated (Fig. [157]5e). We next
investigated if this observation translated into an increase in
activation markers and effector function. As expected, most of the
activation markers studied displayed a significant increase as compared
to neuron-reactive KIR^+CD8^+ T cells from AgDs (HLA-DQA1, HLA-DQB1,
HLA-DRA, HLA-DRB1, CD44, CD69, CD74, ICAM1; Fig. [158]5f).
Interestingly, we observed a significant increase in genes involved in
pro-inflammatory cytokine and chemokine production (IFNG, TNF, CCL3,
CCL4, CSF1). Additionally, these cells displayed a decrease in GZMH
while they retained an important expression of other cytotoxic genes
(GZMK, LAMP1, NKG7) (Fig. [159]5g). Overall, the functional profile of
neuron-reactive KIR^+CD8^+ Treg cells appears to be disrupted in Ri-AIE
with a decrease of markers associated with the regulatory function but
a strong increase in TCR signaling, overall activation and cytokine
production, suggesting a shift toward a more activated and potentially
pathogenic phenotype. In order to assess interindividual variability,
we aggregated all cells for each donor to conduct a pseudobulk analysis
at the donor level. This analysis showed consistent patterns across
multiple donors and evidenced trends confirming the analysis performed
at the single-cell level (Supplementary Figs. [160]5 and [161]6).
Fig. 5. Neuron-reactive KIR^+CD8^+ T cells from cluster 1 in Ri-AIE patients
are strongly activated and express high levels of pro-inflammatory cytokines.
[162]Fig. 5
[163]Open in a new tab
a Volcano plot highlighting all significantly upregulated (orange) and
downregulated genes (blue) between neuron-reactive KIR^+CD8^+ T cells
from Ri-AIE vs AgD. Vertical ticked lines represent the fold-change
threshold set at an average log[2]FC(0.5) for upregulated or
log[2]FC(−0.5) for downregulated genes. Horizontal ticked line
represents the adjusted p value threshold established at 0.05. All
significantly differentially expressed genes from c–h are annotated on
the plot. b Dot plot of KEGG pathway enrichment analysis highlighting
the 5 most enriched pathways according to adjusted p value, in
neuron-reactive KIR^+CD8^+ T cells from Ri AIE vs AgD. The enrichment
score is scaled from blue to orange (strongest score), with each dot
reflecting the percentage of gene overlap relative to each pathway. c–h
Heatmaps displaying selected genes involved in key CD8^+ T cell
functions such as immune regulation (c), TCR activation (d) or
inhibition (e), activation markers (f), pro-inflammatory signaling (g)
or TOX-controlled genes (h). Highly expressed genes are represented in
orange and low-expressed genes in blue. A star is displayed in the
column for neuron-reactive KIR^+CD8^+ T cells from Ri-AIE when genes
from this group were significantly differentially expressed as compared
to neuron-reactive KIR^+CD8^+ T cells from AgDs.
Additionally, we compared CD8^+ T cells from Ri01 during disease and
during clinical remission (5 months later, when the patient was treated
by mycophenolate mofetil and corticosteroids) to explore if the
neuron-reactive CD8^+ T cell clonotypes identified during disease would
present with phenotypical differences during remission. Due to the
limited number of cells analyzed, we found very few dysregulated genes
between the two timepoints (Supplementary Fig. [164]7a). Specifically,
FOSB and JUND were the two most dysregulated genes, both significantly
increased at the disease timepoint. Taking into account the most
dysregulated genes in Ri-AIE, we could observe that the cells from Ri01
at disease peak mostly segregated together from the cells from Ri01 at
remission suggesting global changes in the gene expression profile
despite a low individual significance (Supplementary Fig. [165]7b).
Strikingly, most gene expression changes in Ri-AIE at disease peak
versus remission mirrored the dysregulation found in neuron-reactive
CD8^+ T cells from Ri-AIE versus AgDs (Supplementary Fig. [166]7c).
These data suggest a global reverting of the pathogenic phenotype of
neuron-reactive CD8^+ T cells concomitant with clinical improvement.
Last, since TOX was one of the key transcription factors associated
with cluster 1 (Fig. [167]4g, Supplementary Data [168]2), and as it
plays a major role in T cell exhaustion and triggering an
encephalitogenic program in CD8^+ T cells, we looked at the expression
of genes controlled by TOX^[169]28. Some genes known to be upregulated
by TOX (ZFP36L1, NFKBIA) were also upregulated in neuron-reactive
KIR^+CD8^+ T cells from Ri-AIE, while the genes downregulated by TOX
mostly displayed a trend to decrease (only ID2 was significant)
(Fig. [170]5h). These data again suggest that TOX is active in this
subset of neuron-reactive CD8^+ T cells.
Having demonstrated the effector and activated phenotype of
neuron-reactive KIR^+CD8^+ T cells in Ri-AIE as compared to AgD, we
addressed one critical question: are these cells present in the CNS?
Indeed, to be able to trigger symptoms in Ri-AIE patients, these cells
would have to be present in the brains of patients. As we were able to
obtain autopsy tissue for one RI-AIE patient from our cohort (Ri02), we
looked for the presence of cytotoxic CD8^+ T cells in the lesions of
this patient as compared to age-matched controls (Fig. [171]6a, b). We
observed a massive CD8^+ T cell infiltration (mean of 7 CD8^+ T
cells/mm^2) in Ri02 patient as compared to five age-matched controls
(mean of 1 CD8^+ T cell/mm^2; Fig. [172]6c). Supporting a role for TOX
in inducing an encephalitogenic program in CD8^+ T cells^[173]28, we
found that 58.8% of CD8^+ T cells in these brain lesions were positive
for TOX (Fig. [174]6d). Additionally, 82.2% of CD8^+ T cells in the
lesions were GzmB^+ and affixed to neurons (Fig. [175]6e).
Fig. 6. Cytotoxic TOX^+CD8^+ T cells infiltrate the brain in Ri-AIE.
[176]Fig. 6
[177]Open in a new tab
a Representative immunostaining of brain tissue from one aged-matched
control. Brain tissue was stained for CD8 (yellow) and DAPI (blue). Bar
length represents 20 μm. b Immunostaining of a brain lesion in autopsy
tissue from Ri02. Left panels: Brain tissue was stained for TOX (red),
CD8 (yellow) and nuclei (blue). Bar length represents 20 μm. Right
panels: Brain tissue was stained for GZMB (magenta), CD8 (yellow), and
nuclei (blue). Bar length represents 25 μm. c Quantification
(cells/mm^2) of brain-infiltrating CD8^+ T cells in Ri02 (orange) vs
aged-matched donors (n = 5, blue). Each dot represents one individual
sample. Bar height represents the mean ± SEM. d Quantification of the
proportion of TOX^+CD8^+ T cells among total brain-infiltrating CD8^+ T
cells for Ri02. e Quantification of the proportion of GZMB^+CD8^+ T
cells among total brain-infiltrating CD8^+ T cells for Ri02.
Overall, our results demonstrate that while blood-circulating
neuron-reactive KIR^+CD8^+ T cells are commonly present in aged
individuals, those of Ri-AIE patients have lost their regulatory
phenotype, are more activated and are present in the brain.
Importantly, this disease-associated phenotype was partially reverted
in CD8^+ T cells from one of these patients taken during clinical
remission. Altogether, these findings assert the pathogenesis of
autoreactive CD8^+ T cells in Ri-AIE.
Discussion
Here, we report on an unbiased novel method to identify
neuron-autoreactive CD8^+ T cells in a human-based and autologous
system. The antigen-presenting cells used in this technique are the
cells naturally producing the antigens in the body and, therefore, can
present the broadest range of antigens with the right
cell-type-associated post-translational modifications and splicing.
Indeed, such antigen modifications have been demonstrated to strongly
influence T cell antigenic recognition in cancer^[178]29, and it has
been known for a long time that citrullination, for example, plays a
role in antigen recognition in autoimmune diseases^[179]30. In
addition, by using autologous neurons, we can simultaneously screen for
T cell recognition against all relevant HLA alleles for the studied
cohort.
Applying this method to first screen for the presence of
neuron-reactive CD8^+ T cells in young HDs (median age 36 years old),
we could uncover that six out of six donors demonstrated expansion of
specific T cell clonotypes upon coculture with neurons. Further
validation of individual TCRs showed that expanded CD8^+ T cells in
these conditions are indeed neuron-reactive. Although it has been
previously shown that certain HDs may harbor hypocretin neuron,
astrocyte or oligodendrocyte-reactive CD8^+ T
cells^[180]23,[181]31,[182]32, these results highlight that the
presence of circulating neuron-reactive CD8^+ T cells is a highly
common feature of the human TCR repertoire. Our data demonstrate that
they are most strikingly present at very low frequencies in all young
HDs studied (mostly below 0.01%, Fig. [183]2c). Of note, identification
of these neuron-reactive CD8^+ T cells in young HDs was possible only
thanks to the very high sensitivity of our assay which depends only on
the number of T cells used as input and demonstrated sensitivity
superior to 0.001% (with an input of 10^5 CD8^+ T cells). In
comparison, conventional methods are mostly limited to frequencies
above 0.01%^[184]18. As such, the methodology described here holds
great promise to study the CD8^+ T cell repertoire in patients with
autoimmune diseases but also in HDs, thus providing the scientific
community with the right tools to address fundamental questions on the
development of autoreactive CD8^+ T cells and how they can go rogue in
autoimmunity.
In the second part of this study, we focused our analysis on the
identification of neuron-reactive CD8^+ T cells in a larger cohort of
three aged control donors without autoimmune disease (AgDs, median age
70.5 years old) and seven aged-matched Ri-AIE patients (median age 69
years old). Again, neuron-reactive CD8^+ T cells were identified in all
donors, but contrasting with the results from younger donors, ex vivo
neuron-reactive CD8^+ T cells were more abundant in Ri-AIE and AgDs
(ranging from 0.01% to 6.47%, Supplementary Fig. [185]4b). Of note,
there was no difference in terms of frequencies of neuron-reactive
CD8^+ T cells between AgDs and Ri-AIE. Due to the partially HLA-matched
system we used to assess TCR reactivity, we cannot rule out that
certain neuron-reactive CD8^+ T cell clonotypes may have been missed
due to incomplete HLA matching. Nevertheless, the similar proportion of
neuron-reactive CD8^+ T cell clonotypes between AgDs and Ri-AIE
patients mitigates this concern.
Resorting to single-cell transcriptomic analysis coupled with TCR
sequencing, we uncovered that these autoreactive clonotypes belonged to
a subset of CD8^+ T cells expressing the KIR family and the
transcription factor Helios (IKZF2). These markers are characteristic
of KIR^+CD8^+ Treg cells. They have been shown to be expanded in aging,
infection, cancer and various autoimmune
diseases^[186]25,[187]33,[188]34. KIR expression on CD8^+ T cells plays
a role in long-term survival as well as controlling TCR activation to
prevent excessive and deleterious effector functions^[189]35. While the
antigen specificity of KIR^+CD8^+ Treg cells has not been fully
elucidated, a few studies reported that they most likely recognize
autoantigens through classical TCR-HLA class I (either A, B, C) or
HLA-E interactions^[190]25,[191]36,[192]37. Interestingly, recent
studies demonstrated that one of the key targets of KIR^+CD8^+ Treg
cells is CD4^+ T cells, in particular autoreactive ones, which
contribute to preventing autoimmunity^[193]25. In cancer, KIR^+CD8^+
Treg cells infiltrate tumors and are associated with a bad prognosis
since they are acting on other immune cells to dampen the immune
response against tumors^[194]27. These seminal studies contributed to
identifying KIR^+CD8^+ T cells as a novel Treg subset acting through
cytotoxic effector functions^[195]25,[196]27.
Interestingly, KIR^+CD8^+ T cells can be increased in autoimmune
diseases, raising the question of their actual regulatory capacities in
these diseases^[197]38. Actually, phenotypic differences of KIR^+CD8^+
Treg cells in the healthy state versus autoimmune diseases have not
been thoroughly described. In the present study, we show that
KIR^+CD8^+ T cells can recognize neurons, notably in the context of
Ri-AIE, a disease in which autoreactive CD8^+ T cells are suspected to
be the main pathogenic effectors^[198]2. Strikingly, we find in the
single cell analysis that the expression of KIR genes (in particular
the KIR2DL family), IKZF2 and genes involved in inhibiting TCR
downstream signaling are significantly decreased in neuron-reactive
CD8^+ T cells from the Ri-AIE group as compared to aged-matched
controls. Concomitantly, these cells display strong TCR signaling
coupled with increased expression of activation markers and cytokine
production, thus demonstrating increased effector functions.
In line with our findings, Li et al. reported increased expression of
activation and cytotoxic markers in low KIR-expressing CD8^+ T cells vs
high KIR-expressing CD8^+ T cells^[199]25. Of importance, this study
explored the role of KIR^+CD8^+ Treg cells in various autoimmune
conditions, including multiple sclerosis (MS), the most frequent
neurological autoimmune disease. Strikingly, KIR^+CD8^+ T cells in MS
were characterized by the increase of a specific subset displaying
strong IFN signaling^[200]25. Mirroring this finding, we found a
specific gene set related to IFN signaling to be increased in
neuron-reactive KIR^+CD8^+ T cells from Ri-AIE. Of note, all Ri-AIE
patients but one suffered from cancer as an underlying cause of AIE.
Yet, it is suspected that the autoreactive CD8^+ T cells responsible
for AIE are primed within tumors before targeting the CNS. It has been
demonstrated that tumors from patients suffering from AIE with anti-Hu
antibodies, another CD8^+ T cell-mediated AIE, were characterized by
increased IFNγ signaling, mirroring our finding of high IFN signaling
in neuron-reactive KIR^+CD8^+ T cells in Ri-AIE^[201]39. Altogether,
our results raise the question whether the microenvironment of some
tumors may provide high TCR stimulation together with IFN signaling to
infiltrating KIR^+CD8^+ Treg cells. The latter cells would, in turn,
downregulate KIRs, overruling inhibitory control, thus gaining the
ability to cause AIE by directly recognizing neurons through their TCR.
Interestingly, our results demonstrate that these KIR^+CD8^+ T cells
produce TCRs able to recognize both neurons and immune cells, albeit at
a lower magnitude. Interestingly, a similar cross-reactivity has
previously been demonstrated for CD4^+ T cells in the context of MS,
with some CD4^+ T cells recognizing the RASGRP2 antigen expressed by B
cells and cortical neurons^[202]40. Given that KIR^+CD8^+ Treg cells
are known to recognize autoreactive CD4^+ T cells through their TCR, by
analogy, we suggest that dysregulated CD8^+ T cells in AIE may not only
recognize immune cells, but also neuronal antigens^[203]25. However, to
be more assertive, the specificity of these autoreactive KIR^+CD8^+ T
cells would have to be studied more in depth, especially because 15% of
the neuron-reactive TCRs we identify recognize only neurons and not
PBMCs.
We also found that TOX was one of the transcription factors associated
with the KIR^+CD8^+ T cell cluster in our dataset. Interestingly, TOX
is mostly known in the context of chronic infection and cancer, in
which it plays the dual role of enhancing long-term survival of CD8^+ T
cells but also driving T cell hyperresponsiveness through
exhaustion^[204]41,[205]42. This functionality is extremely similar to
the KIR family receptors, suggesting that both pathways may be linked.
Most importantly, TOX is a key regulator of the encephalitogenic
program in autoreactive CD8^+ T cells, as demonstrated in experimental
models of brain autoimmunity^[206]28. Furthermore, TOX^+CD8^+ T cells
have been found in the brain parenchyma of patients with AIE, as well
as in MS, thus suggesting a strong role of this factor in neurological
autoimmune disorders^[207]28,[208]43. As a matter of fact, the
neuron-reactive KIR^+CD8^+ T cells we identified in the blood of Ri-AIE
patients share some markers with encephalitogenic autoreactive CD8^+ T
cells in these models. In particular, we find dysregulation of
downstream genes directly regulated by TOX. Moreover, we also
demonstrate that TOX^+CD8^+ T cells are found in the lesions of a
Ri-AIE patient (Ri02) for whom we had autopsy brain tissue, thus
confirming previous findings pertaining to TOX association with AIE.
Taken together, our findings suggest that in AIE, autoreactive
KIR^+CD8^+ T cells most likely shift from their original purpose of
containing autoimmunity towards infiltration of the brain, thus
contributing to the pathogenesis of neurological autoimmune disorders.
Functional studies would be warranted to further explore how these
autoreactive KIR^+CD8^+ T cells directly cause the damage seen in
Ri-AIE lesions. We demonstrate that neuron-reactive clonotypes
downregulate inhibitory markers and display a specific gene signature
of highly activated cytotoxic CD8^+ T cells together with a signature
reminiscent of the TOX-induced encephalitogenic program. Of note, we
observed some degree of variability among Ri-AIE patients with
alterations in the aforementioned pathways being more marked in some
patients than others, thus warranting further confirmation in a larger
cohort of patients. Indeed, while statistical analysis at the single
cell level revealed an interesting set of genes significantly
dysregulated, statistical analysis at the patient level in a
pseudobulk/mixed-model analysis (3 AgDs vs 5 Ri-AIE) did not identify a
significant difference, most likely because of limited sample size and
uneven cell numbers.
Here, we focused on the study of KIR^+CD8^+ T cells due to the initial
identification of a neuron-reactive clonotype belonging to this cell
population in Ri01. However, we cannot exclude that other CD8^+ T cell
populations may also play a role in Ri-AIE, for instance cluster 6 was
significantly enriched in Ri-AIE patients (Supplementary Fig. [209]3c).
Finally, our coculture method based on using hiPSC-derived as APCs has
the potential to advance the understanding of pathogenic CD8^+ T cells
in neurological autoimmune diseases, paving the way for significant
insights into this intricate field, and suggests that hiPSC-derived
somatic cells could be used as antigen-presenting cells to study a
large variety of other autoimmune diseases.
Methods
Study population
Blood samples from six healthy donors (HDs), three AgDs and seven
patients with anti-Ri-AIE were used in this study (Supplementary
Table [210]4). Blood samples were collected across three centers
[Laboratory of Neuroimmunology (Lausanne University Hospital and
University of Lausanne); Department of Neurology with Institute of
Translational Neurology (University of Münster, Germany); and the
French Reference Center on Paraneoplastic Neurological Syndrome
(Université Claude-Bernard, Lyon, France)]. For brain tissue, one
Ri-AIE patient (Ri02, age 70) and 5 age-matched controls (Department of
Pathology and Immunology, University of Geneva) (F/M ratio: 2/3, median
age 70) were included. All donors gave their written informed consent
according to regulations established by the responsible ethics
committees (Lausanne, Project COOLIN’BRAIN, CER-VD 2018-01622; Geneva,
Project n° 2017-01737; Ethics committee of the University of Münster
registration nos. 2013-682-b-S and 2016-053-f-S; Institutional review
board of the Hospices Civils de Lyon). PBMCs from each donor were
obtained by standard Ficoll-Paque (Sigma-Aldrich) gradient
centrifugation, and cells were liquid nitrogen-frozen in fetal bovine
serum (FBS, Biowest) and DMSO (1:10, Sigma-Aldrich)^[211]44. PBMCs from
all AIE patients were taken during diagnostic workup when symptoms were
present and patients were untreated, with an additional timepoint at
remission also taken for Ri01. For HLA typing, genomic DNA was
extracted from PBMCs, and HLA genes were amplified by polymerase chain
reaction (PCR). Nextera adapters were added by tagmentation, and the
resulting libraries were sequenced on the MiniSeq instrument
(Illumina). Sequencing data were then analyzed with the Assign TruSight
HLA v.2.1 software provided by CareDx^[212]45.
Generation and characterization of human-induced pluripotent stem cell
(hiPSC)-derived neurons and precursors
Human iPSCs were generated as part of the Lausanne biobank
(BB_007_BBH-NI). For all six HDs and one Ri-AIE patient (Ri01), hiPSCs
were reprogrammed from CD71^+ cells isolated from PBMCs and passed all
standard quality controls required (microbiology, pluripotency,
differentiation capacity, genomic integrity, episome
clearance)^[213]46,[214]47. Human iPSCs were differentiated into neural
precursor cells (NPCs)^[215]46,[216]48, and mature neurons were then
obtained through transduction of NPCs with an NGN2 lentiviral vector as
described by Ho et al.^[217]22 and used in previous
publications^[218]49,[219]50. Human iPSC-derived neurons were
characterized by immunohistochemistry as follows. First, they were
plated and differentiated in polyornithine (1:5,
Sigma-Aldrich)/laminine (1:500, Sigma-Aldrich)-coated tissue
culture-treated 24-well plates and treated with IFNγ (1 ng/ml, Miltenyi
Biotec) and TNFα (1 ng/ml, R&D Systems) for 48 h to induce HLA class I
enhancement (see Human-iPSC-derived neuron preparation section and
Supplementary Table [220]7). Neurons were washed once with 500 μL of
cold PBS and fixed with PBS + paraformaldehyde (PFA) (4:100, Electron
Microscopy Sciences) for 10 min at 4 °C. Wells were then washed with
blocking buffer (PBS + Normal goat serum (5:100, Jackson
ImmunoResearch) + 0.1% Triton X-100 (Sigma-Aldrich)). Primary
antibodies including rabbit IgG anti-NF200 (1:200, Sigma Aldrich,
polyclonal), chicken IgY anti-MAP2 (1:200, Abcam, polyclonal) and mouse
IgG2a anti-HLA-A, -B, -C (1:500, AffinityImmuno, clone W6/32) were
incubated in 250ul blocking buffer with neurons overnight at 4 °C.
After extensive washing steps, secondary antibodies including
anti-rabbit IgG (H + L) AF546 (Invitrogen), anti-chicken IgY (H + L)
AF546 (Invitrogen) and anti-mouse IgG (H + L) AF488 (Invitrogen) were
added for 30 min at room temperature. Counterstaining with DAPI (1:500,
Sigma-Aldrich) was also performed at this stage (Supplementary
Table [221]8). Then, after additional washing steps, images were
acquired using a Leica DMi8 microscope and post-processed with Leica
LAS X software V5.2.
Human iPSC-derived neuron preparation (HLA enhancement and peptide pulsation)
Neurons were plated in polyornithine (1:5, Sigma-Aldrich)/laminine
(1:500, Sigma-Aldrich)-coated tissue culture-treated 48-well plates
(Corning) at a density of 100,000 cells/cm^2. To induce HLA class I
upregulation, the cell medium was replaced with fresh medium
supplemented with IFNγ (1 ng/ml, Miltenyi Biotec) and TNFα (1 ng/ml,
R&D Systems) for 48 hours. Some experiments required the pulsation of
CNS cells with reconstituted viral peptide pools. To this end, CNS
cells were pulsed with CD8^+ T cell-restricted peptide pools from
either EBV, CMV or VZV (1 μg/ml for each peptide pool, JPT Peptide
Technologies) four hours prior to culture with CD8^+ T cells. EBV and
CMV CD8^+ T cell-restricted peptide pools were reconstituted from
respectively 29 and 45 individual immunogenic peptides (JPT Peptide
Technologies) (Supplementary Tables [222]1 and [223]2). VZV peptide
pools were acquired from a commercially available mix of 63 individual
peptides (PepMix VZV, IE63, JPT Peptide Technologies). Importantly,
prior to overnight incubation with CD8^+ T cells, hiPSC-derived neurons
were carefully washed four times with cell medium to remove any
residual cytokines (i.e., IFNγ or TNFα) or viral peptides.
Neuron-ex vivo CD8^+ T cell overnight culture
Ex vivo PBMC were thawed and rested overnight in a serum-free T cell
expansion medium (SFM, Thermo Fisher Scientific). After resting, CD8^+
T cells were isolated by magnetic-associated cell sorting (MACS) (see
MACS section below), counted and cultured with IFNγ/TNFα-treated
neurons (±peptide pulsation) (see hiPSC-derived neuron preparation
section and Supplementary Table [224]7) at a ratio of 1:1 (i.e.,
100’000 CD8^+ T cells for 100’000 neurons per well). Neurons and
autologous CD8^+ T cells were cultured together overnight, and an IFNy
secretion assay was performed. Regarding IFNγ ELISpot, steps were
performed as per manufacturer instructions^[225]44.
Neuron-PBMC coculture
For all 6 HDs and Ri01, autologous PBMCs were thawed and rested
overnight in SFM. Rested PBMCs were counted, resuspended at 4 million
cells/ml and then cultured with IFNγ/TNFα-treated neurons (see
hiPSC-derived neuron preparation section and Supplementary
Table [226]7) at a density of 1.2 million cells/cm^2 with IL-2
(1000 UI/ml, Miltenyi Biotec) and a CD28 agonist antibody (5ug/ml, BD
Biosciences, clone CD28.2) for a total of 14 days. In total, 300 µl of
fresh SFM and IL-2 (1000UI/ml) were added at day 2 and then renewed at
day 5. At day 7, PBMCs from the coculture were harvested, counted and
resuspended at 4 million cells/ml and then re-cultured with fresh
IFNγ/TNFα-treated neurons. In total, 300 µl of fresh SFM and IL-2
(1000 UI/ml) were added at day 10 and then renewed at day 12. Bulk
TCR-α and -β chain repertoire sequencing was performed directly ex vivo
as well as at days 7 and 14 of coculture (see Bulk TCR-α and TCR-β
chain repertoire sequencing and analysis section and Supplementary
Table [227]7). In some cases, an IFNy secretion assay was performed at
day 14 of coculture and subsequent fluorescence-associated cell sorting
(FACS) was performed to isolate CD3^+CD8^+IFNy^+ fractions (see Flow
cytometry section). Of note, due to the restricted number of PBMCs,
neuron-PBMC cocultures were not performed for any of the AgDs nor for
the remaining six Ri-AIE patients (Ri02-Ri07). Instead, in-depth scRNA
seq was prioritized over hiPSC reprogramming and subsequent coculture
experiments. Indeed, for these patients, PBMC yield was insufficient
to: (1) generate hiPSC-derived neurons, (2) perform the autologous
cocultures.
Magnetic-associated cell sorting (MACS)
Isolation of untouched CD8^+ T cells from total PBMCs was performed
using a two-step human CD8^+ T cell isolation kit (Miltenyi Biotec).
All steps were performed following the manufacturer's instructions.
After MACS, additional purity checks were performed by flow cytometry
(see Flow cytometry section and Supplementary Tables [228]7 and
[229]8).
IFNγ secretion assay
This assay was performed in two separate experiments: (1) Overnight
culture of ex vivo CD8^+ T cells with IFNγ/TNFα-treated neurons
(±peptide pulsation); (2) overnight culture of CD8^+ T cells isolated
after 14 days of neuron-PBMC coculture with IFNγ/TNFα-treated neurons.
Experimental conditions included IFNγ/TNFα-treated neurons or the
addition of a blocking anti-HLA-A, -B, or -C antibody (W6/32, Affinity
Immuno).
IFNγ production of CD8^+ T cells was measured by adapting a
commercially available IFNγ secretion assay kit (Miltenyi Biotec).
Briefly, MACS-sorted CD8^+ T cells were stained with an IFNγ Catch
Reagent prior to overnight culture with neurons. Additionally, an IFNγ
Detection Antibody (1:100) was added to the neuron-CD8^+ T cell culture
prior to overnight incubation. If not otherwise specified, all other
steps and reagent concentrations were applied following the
manufacturer's instructions.
Flow cytometry
For HLA class I assessment, neurons were detached using TrypLE (Gibco)
and washed with phosphate buffer saline (PBS) and FBS (2:100). Cells
were then stained with a pan HLA-A, -B, -C antibody (2:100, Santa Cruz
Biotechnology, clone W6/32), washed again with PBS + 2% FBS and fixed
in PBS + PFA (4:100, Electron Microscopy Sciences).
CD8^+ T cell staining was performed the day after the overnight IFNy
secretion assay or for post-MACS purity checks. Cells in suspension
were harvested and washed with PBS and 2% FBS. Anti-CD8a (2:100, BD
Biosciences, clone RPA-T8) and anti-CD3 (2:100, BD Biosciences, clone
SK7) antibodies were then added, cells were washed again with PBS + 2%
FBS and fixed in PBS + 4% PFA. Viability of all cells was assessed
using an aqua fluorescent reactive amine dye (4:1000, Life
Technologies) (Supplementary Table [230]8). Surface marker expression
was assessed using an LSR II flow cytometer (BD Biosciences) and BD
FACSDiva Software V. Analysis was carried on FlowJo software V11.
When single-cell TCR sequencing was necessary (see “Single-cell TCR-α
and TCR-β chain sequencing” section), after an overnight IFN-γ
secretion assay, CD8+ T cells were sorted by fluorescence-associated
cell sorting (FACS) into IFNγ+CD3+CD8+ T populations at 1 cell/well.
For this, CD8^+ T cells were stained and processed as described above,
and sorting was performed using a FACSAria III cytometer (BD
Biosciences). No PBS-PFA fixation steps were performed in this case.
Bulk TCR-α and TCR-β chain repertoire sequencing and analysis
MACS-isolated CD8^+ T cells were suspended in 300 μl Lysis/Binding
Buffer (Thermo Fisher Scientific), and bulk TCR sequencing analyses
were performed^[231]51. mRNA was isolated by magnetic beads and
amplified by in vitro transcription using the Superscript III enzyme
with primers specific for TCR gene families. A 5′ adapter was added by
multiplex reverse transcription, and TCRs were amplified using one
primer in the adapter and one in the constant region. Libraries were
sequenced on an Illumina instrument, and TCR sequences were processed
using an ad hoc Perl script. The Shannon Entropy was calculated as
follows
[MATH: −∑i=1
nFi*log2
(Fi) :MATH]
1
Where n is the total number of clonotypes and F the clonotype
frequency. Clonality, refers to 1-Pielou index, was calculated as
follows
[MATH: 1−−∑<
mrow>i=1nFi*log10(
Fi)<
/mrow>log10(
n) :MATH]
2
Where n is the total number of clonotypes and F the clonotype
frequency.
A clonotype was considered expanded if its TCR-β chain frequency
presented with a >9 fold-increase between day 14 of coculture and ex
vivo. When TCR-β chains were undetectable ex vivo, the fold-increase
was calculated by assigning a maximal theoretical frequency to the ex
vivo TCR-β chain values (i.e., 1/n° of ex vivo CD8^+ T cells used for
bulk TCR-β chain sequencing).
Single-cell TCR-α and TCR-β chain sequencing (scTCRseq)
For the pairing of the corresponding TCR-α chain, scTCRseq on CD8^+ T
cells at day 14 was performed. For this, IFNy^+CD3^+CD8^+ T cells were
sorted by FACS at 1 cell/well into 96-well PCR plates containing 15 µL
of DNase/RNase-free distilled water (Invitrogen) with 0.2% Triton X-100
(Sigma-Aldrich) and an RNase inhibitor (2 U/µL) (Enzymatics). TCR-α
and-β chains were amplified using OneStep RT-PCR kit (Qiagen) according
to the manufacturer’s recommendations, with the following modification:
a collection covering all V segments and two primers designed in alpha
and beta constant regions were used for the amplification. Then,
amplicons were purified using AmpureXP beads (Beckman Coulter)
according to the manufacturer’s instructions. A second amplification
was performed with the Phusion Hot Start DNA Polymerase (NEB). A
forward primer, designed in the adapter sequence (added during the
RT-PCR) and two reverse nested primers, designed in the constant
regions, were used for the amplification. The PCR mix was composed of
1 µL of purified product, 0.4 µL of 10 mM dNTP mix (Promega), 0.4 µL of
primers mix alpha, 0.4 µL of primers mix beta, 2 µL of buffer and
0.2 µL of polymerase and 5.6 primers mix H[2]O. TCR-α and-β chains were
amplified with the following PCR cycles: 98 °C for 4′, 25× (98 °C for
10′′, 55 °C for 30′′, 72 °C for 30′′), 72 °C for 2′. The PCR product
was purified by adding 1 µL of ExoSAP-IT (Affymetrix) and incubating at
37 °C for 15′ and then at 85 °C for 15′. The third PCR was performed
with the Phusion hot Start (NEB) to add the Illumina adapter and index.
A mix containing 1 µL of 10 mM dNTP (Promega), 5 µL of 0.25 µM
NexteraXT primer index, 3 µL of buffer, 0.2 µL of enzyme and 5.8 µL of
deionized water was prepared and added directly to the purified PCR
product. The second amplification was performed as follows: 98 °C for
4′, 15× (98 °C for 10′′, 55 °C for 30′′ 72 °C for 30′′), 72 °C for 2′.
After purification on AmpureXP beads (Beckman Coulter), libraries were
sequenced on Illumina instruments and sequences extracted using an ad
hoc Perl script. Both chains were amplified, then transfected into
reporter cell lines as described below (see TCR-α and -β chain
amplification, cloning and validation section and Supplementary
Table [232]7).
TCR-α and -β chain amplification, cloning and validation
For all the HDs tested and Ri01, single TCR-α and -β chains were
amplified from residual bulk RNA material^[233]51. Briefly, two primers
were designed in the CDR3 of each TCR to specifically amplify the V and
the J regions. The two amplicons were combined by fusion PCR, and the
constant region was added by a second fusion PCR.
For TCR chains from the three AgDs and Ri02-Ri07 AIE patients, fully
human codon-optimized DNA sequences were synthesized at GeneArt (Thermo
Fisher Scientific) and served as templates for in vitro transcription
(IVT) and polyadenylation of RNA molecules as per the manufacturer’s
instructions (HIScribe T7 ARCA mRNA kit (with tailing), NEB), followed
by co-transfection into recipient T cells.
To validate antigen reactivity, TCR-α/β pairs were cloned into a
recipient Jurkat cell line (TCR/CD3 Jurkat-luc cells (NFAT), Promega,
in-house stably transduced with human CD8^α/β and TCR^α/β
CRISPR-KO)^[234]52. mRNA encoding for the TCR chains was generated
using the HiScribe T7 ARCA mRNA Kit as per the manufacturer’s
instructions. Jurkat cells were electroporated using the Neon
electroporation system (Thermo Fisher Scientific) with the following
parameters: 1,325 V, 10 ms, 3 pulses. Electroporated Jurkat cells were
cultured with IFNγ/TNFα-treated hiPSC-derived neurons at a ratio of 1:1
(i.e., 100,000 Jurkat for 100,000 neurons) in a 48-well plate in 200 μL
SFM. All conditions were run in duplicates. After overnight incubation,
50,000 Jurkat cells were transferred into opaque tissue culture-treated
96-well plates (Corning) and the assay was performed using the Bio-Glo
Luciferase Assay System (Promega). Additional controls include
mock-(transfection with nuclease-free water) transfected Jurkat cells
and culture with IFNγ/TNFα-treated neurons or in the presence of a
blocking anti-HLA-ABC antibody (W6/32, AffinityImmuno). Luminescence
was measured with a Multimode Microplate Reader (BioTek Synergy, Gen 5
software). As a positive control for TCR activation, Jurkat cells were
cultured in the presence of TransAct (i.e., an anti-CD3/CD28 activating
compound., Miltenyi).
The testing of TCR-transfected NFAT Jurkat cells was performed against
neurons from the donor in which the TCR was identified (HD4 and Ri01)
or against HLA-matched donors when we did not have hiPSC-derived
neurons available (Ri02-Ri07). In these cases, the TCR-transfected NFAT
Jurkat cells were tested against hiPSC-derived neurons from other
donors available in our biobank with matched HLA alleles (Supplementary
Table [235]6).
Single-cell RNA and VDJ sequencing
Single-cell RNA and VDJ sequencing were performed on ex vivo CD8^+ T
cells from all three AgDs and all seven Ri-AIE donors. Of note, for
Ri01, two samples were sequenced, one at disease peak and one during
remission 5 months later (under treatment with mycophenolate mofetil)
resulting in a total of eleven assessed samples. CD8^+ T cells
positively sorted by MACS were assessed for viability by AO/PI staining
and counted with a Luna-FX7 Automated cell counter (Logos Biosystems).
A Chromium Next GEM Chip N (10× genomics) was loaded with the
appropriate number of cells, and the sequencing libraries were prepared
with the Chromium Next GEM Single Cell 5′ HT Reagent Kits v2 dual index
following the manufacturer’s recommendations. Briefly, an emulsion
encapsulating single cells, reverse transcription reagents, and cell
barcoding oligonucleotides was generated. After the actual reverse
transcription step, the emulsion was broken, and double-stranded cDNA
was generated and amplified in a bulk reaction. This cDNA was
fragmented, a P7 sequencing adaptor ligated, and a 5′ gene expression
library was generated by PCR amplification. For V(D)J sequencing, a
similar approach was followed except that 2 steps of PCR-based V(D)J
target enrichment were performed prior to fragmentation.
Libraries were quantified by a fluorimetric method, and their quality
was assessed on a Fragment Analyzer (Agilent Technologies). Sequencing
was performed on Illumina NovaSeq 6000 v1.5 flow cells for 28-10-10-90
cycles (read1 - index i7 - index i5 - read2) with 1% PhiX spike in.
Sequencing data were demultiplexed using the bcl2fastq2 Conversion
Software (v. 2.20, Illumina) and primary data analysis performed with
the Cell Ranger Gene Expression pipeline (version 7.1.0, 10× Genomics).
Mapping of VDJ sequences to the gene expression library resulted in an
average total of 97.69% mapped TCR-β chains (AgD1: 97.9%, AgD2: 97.7%,
AgD3: 94.7%, Ri01_dis: 98%, Ri01_5m: 97.9%, Ri02: 97.3%, Ri03: 98.6%,
Ri04: 98.3%, Ri05: 97.8%, Ri06: 99.6%, Ri07: 96.8%) and 63.27% TCR-α
chains (AgD1: 83.9%, AgD2: 73.4%, AgD3: 67.5%, Ri01_dis: 69.2%,
Ri01_5m: 60.7%, Ri02: 56.2%, Ri03: 85.8%, Ri04: 88.3%, Ri05: 49.3%,
Ri06: 42.3%, Ri07: 19.4%).
CD8^+ T cell clustering analysis and cell subtype annotation
Ambient RNA contamination was removed from the CellRanger counts using
Cellbender v0.3.0^[236]53, with the number of cells detected per sample
from the initial CellRanger analysis used as the “expected-cells”
parameter and 25,000 as the “total droplets included” parameter.
TCR-sequences were collated with cell barcodes using scRepertoire
v2.3.2, quantifying all productive TCR chains. Filtered counts
generated by Cellbender were further filtered to select cells with a
single TCR-β chain sequence in the VDJ reads, a maximum of 10%
mitochondrial reads and at least 100 genes expressed; and genes
expressed in at least 10 cells; 109,478 cells (4824–13,569 per donor)
remained after quality filtering. These cells were integrated and
clustered using Seurat’s atomic sketch integration^[237]54 with 5000
cells used for sketching, 20 neighbours considered when selecting
anchors, reciprocal PCA as the integration method, and default values
for all other parameters. UMAPs were run using the sketch integrated
data with the first 30 PCA components and projected onto the remaining
cells.
Histology
For immunofluorescence staining, after antigen retrieval (Sodium
Citrate pH6, 30 min) and blocking of unspecific binding (PBS and FBS
(1:10)), PFA-fixed sections were incubated with primary antibodies
(mouse IgG1 anti-CD8a (1:50, Abcam, clone C8/144B), rat anti-TOX
(Thermo Fisher Scientific, clone TXRX10), mouse IgG2a anti-GZMB (1:20,
Monosan, clone GrB-7). To amplify the signals of TOX, bound antibodies
were visualized with appropriate species-specific Cy5-conjugated
secondary antibodies for anti-rat tyramide signal amplification (TSA).
Nuclei were stained with DAPI (Sigma-Aldrich) (Supplementary
Table [238]8). Immunostained sections were scanned using Pannoramic 250
FLASH II (3DHISTECH) Digital Slide Scanner with objective magnification
of 20×. Positive signals were quantified by a blinded experimenter
using Pannoramic Viewer software (3DHISTECH) and an image analysis
ruleset based on Visiopharm. For representative images, white balance
was adjusted, and contrast was linearly enhanced using the tools
levels, curves, brightness, and contrast in Adobe Photoshop CC. Image
processing was applied uniformly across all images within a given
dataset.
Graphical representation
Schematic representations were created with BioRender.com. Graphical
representations of HLA class I assessments, IFNy secretion assays,
single-cell and bulk TCR sequencing, TCR validation experiments and
KEGG analysis were developed using GraphPad Prism 9 software (Version
9.1.0). For RNA-seq visualization (heatmaps, UMAPs, dotplots, PCAs,
volcano plots and barplots) and custom clonotype quantification, we
used R version 4.4.0 ([239]https://www.R-project.org/) and the
following R packages (DOI: 10.32614/CRAN.package.argparse), circlize v.
0.4.16^[240]55, ComplexHeatmap v. 2.20.0^[241]56,[242]57, ggrepel v.
0.9.6 (10.32614/CRAN.package.ggrepel), hdf5r v. 1.3.12 (DOI:
10.32614/CRAN.package.hdf5r), janitor v. 2.2.1 (DOI:
10.32614/CRAN.package.janitor), Matrix v. 1.7.3 (DOI:
10.32614/CRAN.package.Matrix), patchwork v. 1.3.0 (DOI:
10.32614/CRAN.package.patchwork), rhdf5 v. 2.48.0 (DOI:
10.18129/B9.bioc.rhdf5), scales v. 1.3.0 (DOI:
10.32614/CRAN.package.scales), scRepertoire v. 2.0.7^[243]58, Seurat v.
5.2.1^[244]54,[245]59–[246]62, SeuratDisk v. 0.0.0.9021
([247]https://github.com/mojaveazure/seurat-disk), tidyverse v. 2.0.0
(DOI: 10.21105/joss.01686) and GraphPad Prism® 9 software (Version
9.1.0). Pseudobulked data was used for heatmap visualizations.
Statistical analysis
Statistical analyses were performed using GraphPad Prism 9 software
(Version 9.1.0) and R version 4.4.0 ([248]https://www.R-project.org/).
Paired non-parametric Wilcoxon tests were performed to compare HLA
class I expression (untreated vs IFNγ + TNFα) and ex vivo and day 14
TCR-β chain metrics (clonality and Shannon entropy). Unpaired
Mann–Whitney tests were performed to compare ex vivo TCR-β chain
metrics and frequencies between AgDs, as well as luminescence values
between these two groups. P values < 0.05 were considered significant.
A Pearson correlation test was performed to compare the number of SFU
from the IFNγ ELISpot and the percentage of IFNγ^+CD8^+ T cells from
IFNγ secretion assay. For scRNAseq, differential expression analyses
were performed at the cell level using Seurat’s FindMarkers method
using the default Wilcoxon rank-sum test after removal of genes
encoding the TCR-α and-β chains. For sample-level analyses, we used
Seurat’s Aggregate Expression to calculate pseudobulk counts and DESeq2
(doi:10.1186/s13059-014-0550-8) for testing for differential
expression. In both cases, tests were run via Seurat’s FindMarkers
function, with an average log-fold change cutoff of 0.5 and a
Benjamini-Hochberg false discovery rate of 0.05 used as significance
cutoffs in cell-level analyses (Supplementary Data [249]2 and [250]3).
For dot plots, we used DESeq2’s fpm function directly to calculate
fragments per million for pseudobulk counts, to normalize for
differences in fragment counts between samples.
Reporting summary
Further information on research design is available in the [251]Nature
Portfolio Reporting Summary linked to this article.
Supplementary information
[252]Supplementary Information^ (1.9MB, pdf)
[253]41467_2025_63573_MOESM2_ESM.pdf^ (4.3KB, pdf)
Description of Additional Supplementary Files
[254]Supplementary Data 1^ (13.1KB, xlsx)
[255]Supplementary Data 2^ (6MB, xlsx)
[256]Supplementary Data 3^ (549.5KB, xlsx)
[257]Reporting Summary^ (231KB, pdf)
[258]Transparent Peer Review file^ (755KB, pdf)
Source data
[259]Source Data^ (658.2KB, xlsx)
Acknowledgements