Study approval
All participants provided written informed consent for participation in the study. Ethical approval was obtained from the Institutional Review Boards at La Jolla Institute for Immunology (protocol numbers VD-124, VD-118, VD-155 and VD-171), Massachusetts General Hospital (protocol number 2006P000982), Emory University (protocol number CR003-IRB00078771), University of California, Irvine (protocol number 20163191), National Institutes of Health (protocol number 17N0131), University of California, San Diego (protocol number 120295) and Columbia University Irving Medical Center (CUMC; protocol numbers IRB-AAAQ9714 and AAAS1669). Research activities with samples from Sanguine Biosciences (a fee-for-service, contract research organization) are not considered human participants research under Health and Human Services regulations.
Study participants
Individuals with ALS (n = 40) and healthy control individuals (n = 28) were recruited by Massachusetts General Hospital, Emory University, University of California, Irvine, Sanguine Biosciences and the National Institutes of Health, referred to as the study cohort in the Methods. An additional 14 participants with ALS were included from the University of California, San Diego and served as a validation cohort. Samples from Massachusetts General Hospital were used to perform preliminary experiments and are not included in the data presented in this study. Inclusion criteria for patients with ALS consisted of: (i) a diagnosis of familial or sporadic ALS according to the El Escorial criteria; (ii) aged 20 years or older at the time of symptom onset; and (iii) the ability to provide informed consent. Exclusion criteria included: (i) other major neurological or medical diseases that could cause progressive weakness or cognitive dysfunction; and (ii) an unstable medical condition that would make participation unsafe. Inclusion criteria for age- and sex-matched control individuals consisted of: (i) age including 53–82 to match the ages of individuals with ALS; (ii) sex matching that of individuals with ALS; and (iii) the ability to provide informed consent. Exclusion criteria for control participants were the same as those for ALS, with the addition of self-reported ALS genetic risk factors (that is, ALS in first-degree blood relatives). ALS diagnosis was based on clinical criteria (symptoms and examination findings). Typically, the diagnosis was associated with clinical findings of upper and lower motor dysfunction, a progressive course and a failure of diagnostic tests such as brain and spinal cord magnetic resonance imaging (MRI), electrophysiological testing and routine laboratory studies to identify an alternative cause. If the clinical presentation deviated from these typical features, a neuromuscular specialist with extensive experience in diagnosing ALS was consulted to adjudicate the diagnosis.
Specific clinical information on the participants with ALS was collected, including age and sex, the time since ALS symptom onset, the time when the individual started experiencing symptoms related to their ALS diagnosis, the time after ALS diagnosis and the time of donation after the initial diagnosis of ALS to understand the duration of the disease (Table 1). ALSFRS-R data were used to evaluate the functional status of participants with ALS and monitor functional changes in patients over time. ALSFRS-R data were missing for 7 participants with ALS from the study cohort and all 14 patients from the validation cohort; these were excluded from analyses in which the ALSFRS-R was used. Predicted survival time was obtained using the online ENCALS prediction model31 (http://tool.encalssurvivalmodel.org/), a well-established and widely used survival prediction tool for participants with ALS, originally developed using data from more than 10,000 individuals across several ALS centres in Europe. The classification is based on diagnostic delay (months), progression rate (points decrease on ALSFRS-R per month), forced vital capacity (percentage of predicted capacity based on normative values for sex, age and height), definite ALS (according to El Escorial criteria), frontotemporal dementia (yes or no), C9orf72 repeat expansion (yes or no) and site of onset. The prediction model classifies patients into one of five categories on the basis of predicted survival time: very short, short, intermediate, long or very long. Genetic mutations were noted on an individual basis if genetic sequencing was performed. Twenty-four individuals with ALS were HLA-typed at an American Society for Histocompatibility and Immunogenetics (ASHI)–accredited laboratory at Murdoch University in Western Australia. Typing for HLA class II (DQA1, DQB1, DRB1, DRB3, DRB4, DRB5 and DPB1) was performed using locus-specific PCR amplification, sequencing was done using the Illumina MiSeq platform and the alleles were called using an ASHI-accredited HLA allele caller software pipeline, IIID HLA analysis suite (http://www.iiid.com.au/laboratory-testing/). The full HLA typing data for these patients are provided in Supplementary Table 2.
Individuals with PD (n = 15) were recruited by the Movement Disorders Clinic at the Department of Neurology at CUMC. Inclusion criteria for the patients consisted of (i) clinically diagnosed PD with the presence of bradykinesia and either resting tremor or rigidity; (ii) PD diagnosis between the age of 35 and 80; (iii) history establishing the benefit of dopaminergic medication; and (iv) ability to provide informed consent. Exclusion criteria for PD were: (i) atypical parkinsonism or other neurological disorders; (ii) history of cancer within the past three years; (iii) autoimmune disease; and (iv) chronic immune-modulatory therapy. The recruited individuals with PD all met the UK Parkinson’s Disease Society Brain Bank criteria for PD.
Individuals with AD (n = 15) were recruited from the Alzheimer’s Disease Research Center at CUMC or from PrecisionMed (a fee-for-service, contract research organization). Patients recruited from CUMC were diagnosed by neurologists according to the National Institute of Aging and Alzheimer’s Association criteria24; those recruited from PrecisionMed were diagnosed according to NINCDS-ADRDA criteria23, by a neurologist or internist. The donors with AD and those with PD were selected to be age- and sex-matched to the donors with ALS.
Isolation of PBMCs
Venous blood was collected from each participant in either heparin or EDTA-containing blood bags or tubes, as previously reported and described. PBMCs were isolated from whole blood by density-gradient centrifugation using Ficoll Paque Plus (GE). In brief, blood was first spun at 800g for 15 min with brakes off to remove plasma. Plasma-depleted blood was then diluted with RPMI, and 35 ml of blood was carefully layered on tubes containing 15 ml Ficoll Paque Plus. These tubes were centrifuged at 800g for 25 min with the brakes off. The interphase cell layer resulting from this spin was collected, washed with RPMI, counted and cryopreserved in 90% v/v fetal bovine serum (FBS) and 10% v/v dimethyl sulfoxide (DMSO), and stored in liquid nitrogen until tested. The detailed protocol for PBMC isolation can be found at protocols.io (https://doi.org/10.17504/protocols.io.bw2ipgce).
Antigen pools
Sets of overlapping peptides spanning the sequences of TDP-43 (101 peptides; NCBI ABO32290.1), SOD1 (29 peptides; UniProt ID P00441), and C9orf72 antigens (100 peptides; UniProt ID Q96LT7). A previously described21 pool encompassing EBV epitopes was used as a control. Peptides were synthesized commercially as crude material on a 1-mg scale by TC Peptide Lab. Lyophilized peptide products were dissolved in 100% DMSO at a concentration of 20 mg ml−1, and their quality was spot-checked by mass spectrometry. These peptides were also combined in ‘megapools’ as described19 and used in the antigen screening experiments. C9orf72 peptides were also tested individually, as described in the main text.
In vitro expansion of antigen-specific cells and FluoroSpot assay
In vitro expansion and subsequent FluoroSpot assays were performed as previously described20. An equal number of ALS and control samples were included per experiment, to reduce the risk of technical biases. The ALS and control donors were randomly assigned to the individual experimental groups. In brief, PBMCs were thawed and then stimulated with neuroantigen or EBV peptide pools (5 μg ml−1) for four days. After four days, cells were supplemented with fresh RPMI and IL-2 (10 U ml−1, ProspecBio), and fed again every three days until day 11. After two weeks of culture, T cell responses to neuroantigen pools were measured by IFNγ, IL-5 and IL-10 FluoroSpot assays. Plates (Mabtech) were coated overnight at 4 °C with an antibody mixture of mouse anti-human IFNγ (clone 1-D1K, Mabtech), mouse anti-human IL-5 (clone TRFK5, Mabtech) and mouse anti-human IL-10 (clone 9D7, Mabtech). A total of 1 × 105 of the collected cells were plated in each well of the coated FluoroSpot plates along with each respective antigen (5 μg ml−1), and incubated at 37 °C in 5% CO2 for 22 h. Cells were also stimulated with 10 μg ml−1 phytohaemagglutinin (positive control) and DMSO corresponding to the concentration in the peptide pool dilutions (negative control) to assess non-specific cytokine production. All conditions were tested in triplicate. After incubation, cells were removed, and membranes were washed. An antibody cocktail containing IFNγ (7-B6-1-FS-BAM), IL-5 (5A10-WASP) and IL-10 (12G8-biotin) prepared in phosphate-buffered saline (PBS) with 0.1% bovine serum albumin was added and incubated for two hours at room temperature. Membranes were then washed again, and secondary antibodies (anti-BAM-490, anti-WASP-640 and SA-550) were incubated for one hour at room temperature. Then, membranes were washed, incubated with fluorescence enhancer (Mabtech) and air-dried for reading. Spots were read and counted using the Mabtech Apex (v.2.0) software on the Mabtech IRIS system. The dilutions of all antibodies used are provided in Supplementary Table 3. Responses were considered positive if they met all three of the following criteria: (i) DMSO background-subtracted SFCs per 106 PBMCs ≥ 100; (ii) stimulation index ≥ 2 compared with DMSO controls; and (iii) P ≤ 0.05 by Student’s t-test or Poisson distribution test. Negative responses were assigned as 100 SFCs per 106 PBMCs, the lower limit of detection of the assay. The total SFCs per donor measurement was obtained by combining the individual IFNγ, IL-5 and IL-10 SFC values for all samples with a positive response. If no positive response was detected for any of the cytokines, the total cytokine response was assigned as 100 SFCs per 106 PBMCs. The average cytokine response was calculated by dividing the individual cytokine SFCs by the total SFCs, and the cytokine ratios were calculated by dividing cytokine SFC values.
HLA II binding predictions
The number of predicted binding events of peptides to the 27 most common HLA-DR, HLA-DQ and HLA-DP class II allelic variants was analysed using the MHC-II Binding Prediction Results tool available at the Immune Epitope Database (IEDB)28. As suggested by the IEDB, we used the NetMHCIIpan-4.1 EL prediction method, and set the cut-off for a binding event as a predicted binding percentile score threshold of 20% or less18. Predicted binding strength was obtained using the NetMHCIIpan-4.1 EL prediction method, and is reported as a normalized rank value compared with peptides from 10,000 randomly selected peptides, with a small value indicating high affinity25.
Inference of HLA restrictions
HLA restrictions were inferred using RATE, hosted by the IEDB25. In brief, RATE infers HLA restrictions by considering the presence or absence of a response to a given epitope as the biological outcome. It calculates the relative frequency of the individuals responding to a given epitope and expressing a given allele, compared with the general test population, and the associated statistical significance. Because spurious results can be observed for HLA alleles in linkage disequilibrium, peptide–HLA associations were validated using the NetMHCIIpan-4.1 EL method, with a percentile score threshold of 30% or less, to validate that the peptides were predicted to bind to their corresponding HLA allele.
Flow cytometry
Spectral methods (Cytek Aurora)
Cells were washed, counted and plated in a 96-well plate at a density of 1 × 106 cells per well. Cells were then stained with a mixture of the following antibodies: fixable viability dye eFluor 506 (Thermo Fisher Scientific), CD4-APC-eF780 (clone: RPA-T4, Thermo Fisher Scientific), CD8-BUV496 (clone: RPA-T8, BD Biosciences), CD20-BV563 (clone: 2H7, BD), CD56-APC (clone: 5.1H11, BioLegend), gdTCR-BV421 (clone: 11F2, BD), CCR4-PE Cy-7 (clone: IG1, BD), CD16-PE Cy5 (clone: 3G8, Thermo Fisher Scientific), CD14-BV480 (clone: M5E2, BD), HLA-DR-AF700 (clone: LN3, Thermo Fisher Scientific), CD161-BV650 (clone: DX12, BD), CXCR3-PE (clone: G025H7, BioLegend), CD19-BV605 (clone: HIB19, BioLegend), CD38-PerCP-Cy5.5 (clone: HIT2, BD), CD3-BUV805 (clone: UCHT1, BD), CCR7-BV785 (clone: G043H7, BioLegend), CCR6-BUV395 (clone: 11A, BD), CD26-FITC (clone: BA5b, BioLegend), CD127-PEFire700 (clone: A019D5, BioLegend), CD45-PE Dazzle594 (clone: HI30, BioLegend), CD25-BV711 (clone: M-A251, BioLegend) and CD45RA-BV570 (clone: HI100, BioLegend), for 20 min at 4 °C in the dark. The dilutions of all antibodies used are provided in Supplementary Table 3. Stained cells were washed twice and resuspended in 100 µl PBS to be run on the Cytek Aurora System (Cytek). FCS files produced from the Cytek Aurora flow cytometer, using the SpectroFlo flow cytometry software (Cytek,v.3.3), were then analysed using FlowJo software (v.10.10.0, Tree Star).
ICS methods (Fortessa X-20)
Antigen-specific cells were expanded for two weeks as described above. On day 14, cells were washed, counted, plated in a 96-well plate at a density of 1 × 106 cells per well, and restimulated with the C9orf72 megapool. After a two-hour incubation, cells were treated for an additional 4 h with GolgiPlug (BD) and GolgiStop (BD). Cells were then washed and stained with a mixture of the following antibodies: fixable viability dye eFluor 506 (Thermo Fisher Scientific), CD4-APC-eF780 (clone: RPA-T4, Thermo Fisher Scientific), CD3-AF700 (clone: UCHT1, BD) and CD8-BV650 (clone: RPA-T8, BioLegend). Cells were incubated for 30 min at 4 °C. Cells were then washed and fixed and permeabilized using the Cyto-Fast Fix/Perm buffer (BioLegend) for 20 min at room temperature. After permeabilization, cells were stained with the following mixture: IL-10-APC (clone: JES3-19F1, BioLegend), IL-4-BV421 (clone: MD425D2, BioLegend), IFNγ-FITC (clone: 4S.B2, Thermo Fisher Scientific) and IL-17-BV785 (clone: BL168, BioLegend) for 20 min at room temperature in the dark. The dilutions of all antibodies used are provided in Supplementary Table 3. Stained cells were then washed twice and resuspended in 100 µl PBS to be run on the Fortessa X-20 flow cytometer (BD). FCS files produced from the Fortessa X-20, using FACSDiva (v.9.2), were then analysed using FlowJo software. The average proportion of each cytokine for each donor was determined by dividing the frequency of cells releasing each cytokine by the total number of cells releasing any of the three cytokines for each donor.
Statistical analysis
Statistical analyses were performed and graphs were created using GraphPad Prism’s descriptive statistics, two-tailed Mann–Whitney test, one-way ANOVA with Dunnett’s multiple comparisons test, two-tailed Fisher exact test and Spearman’s r test as applicable (GraphPad Prism, v.10).
Reporting summary
Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.
