Amyotrophic lateral sclerosis (ALS) is a heterogenous neurodegenerative disorder that affects motor neurons and voluntary muscle control1. ALS heterogeneity includes the age of manifestation, the rate of progression and the anatomical sites of symptom onset. Disease-causing mutations in specific genes have been identified and define different subtypes of ALS1. Although several ALS-associated genes have been shown to affect immune functions2, whether specific immune features account for ALS heterogeneity is poorly understood. Amyotrophic lateral sclerosis-4 (ALS4) is characterized by juvenile onset and slow progression3. Patients with ALS4 show motor difficulties by the time that they are in their thirties, and most of them require devices to assist with walking by their fifties. ALS4 is caused by mutations in the senataxin gene (SETX). Here, using Setx knock-in mice that carry the ALS4-causative L389S mutation, we describe an immunological signature that consists of clonally expanded, terminally differentiated effector memory (TEMRA) CD8 T cells in the central nervous system and the blood of knock-in mice. Increased frequencies of antigen-specific CD8 T cells in knock-in mice mirror the progression of motor neuron disease and correlate with anti-glioma immunity. Furthermore, bone marrow transplantation experiments indicate that the immune system has a key role in ALS4 neurodegeneration. In patients with ALS4, clonally expanded TEMRA CD8 T cells circulate in the peripheral blood. Our results provide evidence of an antigen-specific CD8 T cell response in ALS4, which could be used to unravel disease mechanisms and as a potential biomarker of disease state.
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We thank N. Zhao and S. Zheng from the I.M. laboratory for critical inputs of the study; all the teams at ISMMS for sharing reagents; E. Drapeau for teaching the use of the rotarod; T. Kraus for use of the Luminex 100/200 plate reader; S. Cuadrado-Castano and A. Javaher for help with the B16 melanoma model; the Flow Cytometry and Mouse facilities for training and animal care, and the NGS Platform of the Center for Advanced Genomics Technology for SMART-sequencing; T. Dawson, D. D’souza, B. Upadhyaya and all the team of the Human Immune Monitoring Center for CITE-sequencing and mass cytometry acquisition; and A. Soto, M. Garcia-Barros and the Biorepository and Pathology Dean’s CoRE for assistance with histology. We are grateful to L. Manganaro, J. Moretti and A. Chan for their help in the preliminary phase of the project; M. J. Miller and M. F. Lavin for Setx-deficient mice; the Genomic and Microarray Core Facility of University of Texas Southwestern Medical Center for the autoantigen microarray analysis ; the Duke Electron Microscopy Service of the Duke University Pathology Core for ultrathin sections of axons; The Johns Hopkins ALS Postmortem Core and K. Wilsbach and K. Gallo for providing post-mortem human tissues; and the New York Blood Center for providing buffy coats. We are indebted to ALS4.org for help and support. This work was supported by The Burroughs Wellcome Fund 1017892 (I.M.); the Chan Zuckerberg Initiative Neurodegeneration Challenge Network: the Ben Barres Early Career Acceleration Awards (to I.M., 2018-191895, and N.J., 2018-191856 (5022)) and the Collaborative Science Award (to A.R.L.S., 108313-00002); the Hirschl Young Investigator fellowship (I.M.); National Institutes of Health grants U01AI150748, R01AI143840 and R01AI168130 (I.M.), T32 AI007647 and T32 HD075735 (Y.F.), R33CA225539 and R01AG067581 (N.J.), R35 NS122140 (A.R.L.S.), T32 AG00096 (F.A.), 5R01NS106236 (N.A.S.), R01HL153974 and U01AI150748 (M.B.); the start-up fund of the School of Engineering and Applied Science at University of Pennsylvania (N.J.); and ARISLA Italy, ALS Association ALSA, USA, and the Italian Ministry of Health CCM2011 (C.L.). M.S. received support from the Seve Ballesteros Foundation. J.S.Y.H. is supported by the Charles H Revson Foundation Biomedical Science Fellowship. M.G.-F. is a recipient of a post-doctoral fellowship from the Fundación Alfonso Martín Escudero.
C.L. is the scientific director of the company NEMO Lab, and he served on a scientific advisory board for Mitsubishi Tanabe Pharma Europe, Cytokinetics, Neuraltus and Italfarmaco. The other authors declare no competing interests.
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Extended data figures and tables
a, Average latency to fall (sec) from an accelerating rotarod of WT and KI mice tested at 6 and 8 months of age (2 independent experiments, n = 11 (WT 6 months and KI 8 months) and n = 13 (WT 8 months and KI 6 months) individual mice per group; mean +/− s.e.m.). P value calculated using the one-way Repeated Measures ANOVA (**P = 0.0012) and Bonferroni’s post-test. (b,c) Bone marrow derived dendritic cells (BMDCs) from Setx WT and KI (b,c), and HET and knockout (KO) (b) mice were infected with Citrobacter rodentium (multiplicity of infection = 10, b) or stimulated with 5 μg/ml of cGAMP (c). Bar graphs show the relative induction of the indicated transcripts by RT–qPCR analysis at 2 h post-infection or cGAMP stimulation in KO and KI cells normalized to their controls (2 independent experiments, n = 4 mice/group, mean +/− s.e.m.). No expression of the indicated genes was detected in uninfected cells. d, Concentration of the indicated cytokines measured by Luminex Assay in the serum of KI and WT (8-9 months old) mice (1 out of 2 independent experiments, n = 6 (WT) and n = 5 (KI) mice/group, mean +/− s.e.m.). e, RT–qPCR analysis for the indicated inflammatory genes in the spinal cord of 10 months old WT and KI mice (Log2 relative expression against Actb, 2 independent experiments, n = 5 mice/group, mean +/− s.e.m.). f, Absolute numbers of indicated immune cell subsets in the spleen of 8-9 month-old KI and WT mice. pDC: plasmacytoid dendritic cells; cDC: conventional dendritic cells. g, Expression of the activation marker CD86 in cDC and CD11b+ cells from the spleen of 8-9 months old WT and KI mice. (f,g) 2 independent experiments, n = 4 mice/group, mean +/− s.e.m.
Heat maps showing an unsupervised hierarchical clustering based on IgM (top) and IgG (bottom) reactivity against 128 self-antigens in the serum of 10–12-month-old KI and WT mice (n = 5 mice/group).
a,b, Peripheral blood cells from 8-month-old WT and KI mice were analysed by mass cytometry. a, t-SNE plots after gating on live CD45high (top) and CD19−NK1.1−CD11b−CD11c−TCRβ+ (bottom). b, Frequency of PD-1+ expressing cells after gating on CD44+ CD8+ T cells. Three mice/group were pooled for mass cytometry analysis. c, Gating strategy for flow cytometry analysis of CD8 T cells in the CNS. d, Frequency of PD-1+ CD8 T cells in the spleen and lungs of WT and KI mice at the indicated ages (2 independent experiments, 4 mice/group; mean +/− s.e.m.). e, Frequency of PD-1+ (left) and Foxp3+ (right) CD4 T cells in the peripheral blood of WT and KI mice at the indicated ages (3 independent experiments, n = 6 (left) and 2 independent experiments, n = 4 (8 months) and n = 6 (right) individual mice/group. SB=super bright.
a, Expression of indicated surface markers in CD8 T cells from the spinal cord (top), brain (middle) and peripheral blood (bottom) of 10–12-month-old KI mice after gating on PD-1+ and PD-1− CD8 T cells. Histograms are representative of 3 independent experiment (n = 6 mice). b, Median fluorescence intensity (MFI) of the indicated markers in CD44+CD62L− PD-1+ and PD-1− CD8 T cells isolated from the spinal cord (top) and blood (bottom) of 10–12-month-old KI mice (2 independent experiments, n = 6 (blood TIGIT and TOX), n = 5 (spinal cord TIGIT and TOX), n = 4 (TCF-1) individual mice/group, mean +/− s.e.m.). P value calculated using a two-tailed unpaired t-test with Welch’s correction (spinal cord: ***P = 0.0007; *P = 0.045; **P = 0.0066; blood: ***P = 0.0004 (TOX); ***P = 0.0002 (TIGIT and TCF-1). c, KI mice were crossed to OT-I mice and the offspring analysed at 10 months of age. Dot plots from spinal cords, SC (left), and bar graphs (right) show the frequency of PD-1+ among OVA specific (gated on Vα2+Vβ5+) and non-TCR transgenic (gated on Vα2−) CD8 T cells (3 independent experiments, n = 6, brain and spinal cord, and n = 5, blood, individual mice; mean+/− s.e.m.). P value calculated using a two-tailed unpaired t test with Welch’s correction. **P = 0.0031 (brain); ***P = 0.0004 (SC); ***P = 0.0003 (blood). eF=eFluor.
a, Kinetics of tumour growth in 10–12-month-old KI and WT mice subcutaneously injected with B16-F10 cells. Two independent experiments, n = 10 individual mice/group; mean+/− s.e.m. ns = not significant, P value calculated using a two-tailed Wilcoxon matched-pairs signed rank test. b, Scans of CD8 staining inside glioma isolated from 3 individual WT and KI from 2 independent experiments at day 27 post-tumour detection. c, Spinal cords from 10 to 12-month-old WT (n = 4) and KI (n = 3) mice (top) and in vitro activated WT CD8 T cells (n = 3) (bottom) were analysed by RNA-seq. WT CD8 T cells were used as positive control because increased AS after T cell activation has been reported73. Bar graphs show transcript counts of significantly changed (| deltaPSI | > 0.15, p < 0.05, FDR < 0.05) AS events using mm10 annotation. n = individual mice per group. SE, exon skipping; RI, intron retention; MXE, mutually exclusive exons; A5SS, alternative 5′ splice site; A3SS, alternative 3′ splice site.
a, Schematic of bone marrow cell transplantation experiments. b, Representative dot plots of the frequency of CD45.2 (recipient) and CD45.1 (donor) cells in the peripheral blood of chimeric mice 8 weeks after irradiation and reconstitution. c, Average of motor neuron area calculated in the lumbar region of spinal cord sections. n = 5 mice/group, mean +/− s.e.m. P value calculated using one-way ANOVA Kruskal-Wallis test and Dunn’s post-hoc test (*P = 0.0002). d, Axon areas (left) and number of large calibre axons (right) in the sciatic nerve. n = 6 (WT–WT, KI–KI, KI–WT) and 7 (WT–KI) mice per group; mean +/− s.e.m. P value calculated using one-way ANOVA Kruskal-Wallis test and Dunn’s post-hoc test (*P = 0.026, ns=not statistically significant). Chimeric mice in (c,d) were analysed at 12-13 months after reconstitution. e, Peripheral blood cells from two mice of the indicated group were pooled and analysed by mass cytometry. Left, Details of markers and cell subsets identified by SPADE (spanning-tree progression analysis for density-normalized events) analysis (WT–WT group is shown). Right, SPADE analysis showing the distribution of immune cells into 4 main populations. Size and colour of circles are dependent on the number of cells and the median intensity of expression for each marker, respectively. Red circles highlight PD-1+ CD8 T cells.
Heat maps showing an unsupervised hierarchical clustering based on IgM (top) and IgG (bottom) reactivity against 128 self-antigens in the serum of chimeric mice at 12 months after reconstitution (n = 3 WT–WT and n = 2 KI–KI individual chimeras).
a,d, Cell suspensions from brain, spinal cord, spleen, and peripheral blood of 22–24 month-old FusP517L/WT and FusWT/WT littermates were analysed by spectral flow cytometry. a–c, t-SNE of total live CD45+ cells (a) and frequency of TCRβ+ CD8+ and CD4+ T cells expressing CD62L, CD44, PD-1+ and Foxp3 (b,c) from the spinal cord of FusP517L/WT and FusWT/WT mice after concatenation of all of the 5 samples/group. d, Frequency of CD8 T cell subsets in the indicated organs from the 2 genotypes (2 independent experiments, 5 individual mice/group; mean +/− s.e.m.). e, Frequency of CD8 T cell subsets in the indicated organs from 3-4 month-old non-carrier and SOD1G93A mice by spectral flow cytometry analysis (2 independent experiments, n = 5 (spleen), n = 6 (brain, WT blood) and n = 7 individual mice/group; mean +/− s.e.m.). N= naïve, CD62L+CD44−; CM= central memory, CD62L+CD44+; EM= effector memory CD62L−CD44+. T cells are gated on live CD45high CD19−NK1.1−CD11b−CD11c−TCRγδ−TCRβ+ CD8+ or CD4+ cells.
a, PBMCs from age-matched control individuals and patients were analysed by spectral flow cytometry. Frequencies of naïve (CD45RA+ CD45RO−CD27+CD28+) and central memory (TCM, CD45RO+ CD45RA− CD28+) were determined after gating on CCR7+ CD8 (left) or CD4 (right) T cells. Frequencies of effector (TEff, CD45RA+/− CD45RO+/− CD27+CD28+), effector memory (TEM, CD45RA− CD45RO+ CD27+CD28+) and terminally differentiated effector memory (TEMRA, CD45RO− CD45RA+ CD28−) were determined after gating on CCR7− CD8 or CD4 T cells. T cells were gated on live CD19−CD16− CD56−CD3+ cells. Each dot represents one individual donor and graph show results from 2 independent experiments (n = 5 ALS4 and n = 10 controls). mean +/− s.e.m. P value calculated for each T cell subset using Unpaired two-tailed t test with Welch’s correction (Teff: ***P = 0.0002; TEMRA: ***P = 0.0067). ns= not significant. b, Levels of expression of TOX, TIGIT and TCF-1 in the indicated CD8 T cell subsets from the peripheral blood of patients with ALS4 (n = 4) and age-matched controls (n = 8). Two independent experiments, mean +/− s.e.m. P value calculated by comparing TEMRA CD8 T cells from patients and control individuals pool together to the other subsets using one-way ANOVA and Tukey post-hoc test. c,d, UMAP projections of 20,000 single cells from control individuals (n = 3) and patients with ALS4 (n = 3) coloured by cluster (c) or by cell subsets (d) are shown on the left and Z-score normalized mean expression of differentially expressed genes in the indicated clusters (c) or CD8 T cell subsets (d) are shown on the right.
a,b, UMAP projections of identified clusters showing differential expression of surface markers (by oligo-conjugated antibodies) (a) and of the top genes (b) in ALS4 versus control donors. c, Spectral flow cytometry analysis of the 6 samples used for CITE-seq. Histograms show the frequency of CCR7+ CD8 T cells and dot plots the proportion of the indicated subsets after gating on CCR7pos or neg CD8 T cells as indicated.
Extended Data Fig. 11 Clonal expansion and antigen specificity of TEMRA CD8 T cells from patients with ALS4.
a–c, CD8 T cells from controls and patients with ALS4 were analysed by CITE-seq. a, Donut plots depicting T cell clonality per CD8 T cell subset and per group. b, Donut plots indicating the number of TEMRA CD8 T cells for each indicated clonal category. Each patient and the corresponding age-matched controls are individually shown. c, Z-score normalized mean expression of differentially expressed surface markers (by oligo-conjugated antibodies) in “High” (clonality > 20) versus “Low” expanded TEMRA CD8 T cells from patients with ALS4. “High” and “Low” clones have been subsampled for equal representation on the heat map. d, PBMCs from 2 patients with ALS4 and 4 age-matched control individuals were analysed by spectral flow cytometry using a mixture of fluorophore-conjugated antibodies against 24 human TCR-Vβ. Graph bars show the frequencies of the top 5 TCR VB expressed by TEMRA CD8 T cells in each donor. Top 5 VB chains are indicated in the table below the graph. e, Concentration of IFNγ in the supernatant of PBMCs from control individuals (n = 10) and patients with ALS4 (n = 4) stimulated for 6 days with 15mers overlapping TDP-43 (106 peptides), Senataxin (703 peptides divided in 2 sub-pools), or with a pool of 80 pathogen-derived peptides. Two independent experiments, mean +/− s.e.m.
Extended Data Fig. 12 CD8 T cells are detected in the ventral horn of lumbar spinal cords from patients with ALS4.
CD8 T cell staining in the indicated post-mortem paraffin-embedded tissues from patients with ALS4 and controls. For spinal cord sections, scans show the ventral horn. Narrows indicate CD8 T cells. n = 2.
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Campisi, L., Chizari, S., Ho, J.S.Y. et al. Clonally expanded CD8 T cells characterize amyotrophic lateral sclerosis-4. Nature 606, 945–952 (2022). https://doi.org/10.1038/s41586-022-04844-5