CD4+ effector T cells accelerate Alzheimer's disease in mice

Abstract

Background: Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by pathological deposition of misfolded self-protein amyloid beta (Aβ) which in kind facilitates tau aggregation and neurodegeneration. Neuroinflammation is accepted as a key disease driver caused by innate microglia activation. Recently, adaptive immune alterations have been uncovered that begin early and persist throughout the disease. How these occur and whether they can be harnessed to halt disease progress is unclear. We propose that self-antigens would induct autoreactive effector T cells (Teffs) that drive pro-inflammatory and neurodestructive immunity leading to cognitive impairments. Here, we investigated the role of effector immunity and how it could affect cellular-level disease pathobiology in an AD animal model.

Methods: In this report, we developed and characterized cloned lines of amyloid beta (Aβ) reactive type 1 T helper (Th1) and type 17 Th (Th17) cells to study their role in AD pathogenesis. The cellular phenotype and antigen-specificity of Aβ-specific Th1 and Th17 clones were confirmed using flow cytometry, immunoblot staining and Aβ T cell epitope loaded haplotype-matched major histocompatibility complex II IA^b (MHCII-IA^b-KLVFFAEDVGSNKGA) tetramer binding. Aβ-Th1 and Aβ-Th17 clones were adoptively transferred into APP/PS1 double-transgenic mice expressing chimeric mouse/human amyloid precursor protein and mutant human presenilin 1, and the mice were assessed for memory impairments. Finally, blood, spleen, lymph nodes and brain were harvested for immunological, biochemical, and histological analyses.

Results: The propagated Aβ-Th1 and Aβ-Th17 clones were confirmed stable and long-lived. Treatment of APP/PS1 mice with Aβ reactive Teffs accelerated memory impairment and systemic inflammation, increased amyloid burden, elevated microglia activation, and exacerbated neuroinflammation. Both Th1 and Th17 Aβ-reactive Teffs progressed AD pathology by downregulating anti-inflammatory and immunosuppressive regulatory T cells (Tregs) as recorded in the periphery and within the central nervous system.

Conclusions: These results underscore an important pathological role for CD4+ Teffs in AD progression. We posit that aberrant disease-associated effector T cell immune responses can be controlled. One solution is by Aβ reactive Tregs.

Keywords: APP/PS1 transgenic mice; Alzheimer’s disease (AD); Amyloid beta (Aβ); Effector T cell (Teff); Regulatory T cell (Treg); T cell.

Fig. 1

Cellular phenotype of the Aβ-Th1 and Aβ-Th17 cells. a Flow cytometric analysis of intracellular cytokine and transcription factor expressed by Aβ-Th1 and Aβ-Th17 cells that were maintained as clones for greater than 6 months. T cells were stimulated for 12 h with PMA and ionomycin in the presence of brefeldin A. b Representative immunoblot and quantification for 42 different cytokines and chemokines extracellularly secreted from Aβ-Th1 and Aβ-Th17 cells after stimulation with PMA and ionomycin

Fig. 2

Antigen-specificity of the Aβ-Th1 and Aβ-Th17 cells a MHCII-IA^b–KLVFFAEDVGSNKGA (Aβ T cell epitope) tetramer binding with Aβ-Th1 and Aβ-Th17 cells after incubation. Control tetramer MHCII-IA^b–PVSKMRMATPLLMQA was used for precise gating of Aβ T cell epitope recognizing CD4+ T cell population. b From Aβ-Th1 cells, antigen-recognizing variable regions of T cell receptor (TCR) alpha (α) and beta (β) chains were identified using molecular cloning. Molecular modeling of full-length TCRα/β complex with Aβ_1–42–MHCII-IA^b (pMHC) complex; MHCII-IA^bα chain (green), MHCII-IA^bβ chain (cyan) and peptide (blue); TCRα chain (yellow) and TCRβ chain (red). The interface of MHCII, peptide and TCR binding is shown by encircled region. c (i) peptide surface at the interface of MHC and TCR. Peptide–MHC interactions; (ii) peptide Ala563 and Arg322 interaction with MHCα Arg168 and MHCβ Arg322, respectively; (iii) peptide Lys549 interaction with MHCα Arg168(O); (iv) peptide Lys549 interaction with MHCα Asp169(OD2); TCR–pMHC interactions- (v) pMHC Glu543 and Ser547 interaction with Tyr908, Asp953 and Gln952. (vi) pMHC His535 (NE2) interaction with Asn(O), and His535 (O) interaction with Tyr956 (OH), π–π interactions between Tyr956 and His535; (vii) pMHC interaction with TCRβ, Glu532(OE2)–Tyr961(OH) and Glu532 (OE1)–His886(NE2)

Fig. 3

Aβ-Th1 and Aβ-Th17 cells affect memory function in APP/PS1 mice. a Schematic presentation of the in vivo experimental procedure performed in 4- to 5-month-old female APP/PS1 and age-matched non-Tg mice. n = 6 mice per group were used. b Radial arm water maze (RAWM) test was performed with experimental mice 3 weeks after the first of two adoptive transfers with 1 × 10⁶ Aβ-Th1 or Aβ-Th17 cells intravenously. Errors of 9-day trials were divided into three blocks and averaged for the statistical analysis. Two-way ANOVA was used to determine significant differences between experimental groups. *p < 0.05, **p < 0.01. c Fasting blood glucose concentrations were measured prior to the glucoCEST MRI. d 2-deoxy-glucose (2DG) CEST MRI was performed 5 weeks after the Aβ-Th1 and Aβ-Th17 cells adoptive transfer. Representative MRI images with hippocampal glucose signal are shown for different experimental mice which include baseline MRI scan followed by 2DG injection and thereafter MRI scans every 10 min up to 1 h. n = 4 mice per group were analyzed. Glucose intensity in the hippocampus was calculated as %ΔMTR at different time points compared to the baseline. Area under the curve (AUC) for each mouse was calculated and averaged for statistical significance using one-way ANOVA followed by Newman–Keuls post hoc test. Same line colors and symbols are used to show different groups in b and d

Fig. 4

Adoptive transfer Aβ-Teffs affect systemic inflammation in APP/PS1 mice. Experimental mice were killed 6 weeks after Aβ-Th1 and Aβ-Th17 adoptive transfer. a Frequency of Aβ reactive CD4+ T cells among lymph node cells after stimulation with Aβ_1–42 in presence of feeder cells using fluorescently labeled MHCII-IA^b-peptide tetramer. n = 4 mice per group were analyzed. b Frequency of intracellular pro-inflammatory cytokines TNFα, IFNγ and IL17 from splenocytes after stimulation with PMA and ionomycin in the presence of brefeldin A. n = 6 mice per group were analyzed. c Frequency of CD4+Tbet+ and CD4+RORγ+ T cells in blood, spleen and lymph nodes determined by flow cytometric analysis. n = 6 mice per group were analyzed. One-way ANOVA followed by Newman–Keuls post hoc test was used to determine statistical significance. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001

Fig. 5

Aβ-Teffs affect Treg frequency and function. a Frequency of CD4+CD25+FOXP3+ Tregs in blood, spleen and lymph nodes from n = 6 mice per group. Statistical differences were determined using one-way ANOVA followed by Newman–Keuls post hoc test. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. b Immunosuppressive function of Tregs assessed against proliferating CFSE-stained Tresps isolated from non-Tg mice. Tregs were isolated and pooled from within each group (n = 6 mice per group) and experiment was performed in triplicate. Linear regression analyses of Treg function from non-Tg mice showed r² = 0.28 and p = 0.07. All other APP/PS1 groups showed r² > 0.65 and p < 0.01. Although slops are not significantly different between different experimental groups, Th1 mice showed significantly different intercepts compared to non-Tg (p < 0.01) and APP/PS1 (p < 0.0001) mice. c Transcriptomic analyses for expression of innate and adaptive immune genes was performed using the RNA isolated from hippocampal tissues. Heat maps of fold changes in expression of genes compared to untreated or Aβ-Teff-treated APP/PS1 mice with non-Tg mice (left panel) and APP/PS1/Aβ-Th1 and APP/PS1/Aβ-Th17 mice compared to untreated APP/PS1 mice with significant p value provided in appropriate box (right panel). n = 4 mice per group analyzed using Qiagen RT²-PCR array. d, e Functional and pathway enrichment analysis of transcriptomic dataset was performed using KEGG, Reactome and STRING database. Different immune and inflammatory pathways affected in APP/PS1/Aβ-Th1 and APP/PS1/Aβ-Th17 mice were plotted as a bar chart in comparison to non-Tg (d) and untreated APP/PS1 mice (e). Significant pathways with p value passing Bonferroni-corrected significant level of 0.05 were plotted

Fig. 6

Aβ-Th1 and Aβ-Th17 cells increase amyloid load in APP/PS1 mice. a Western blot analysis performed to determine expression of full-length APP using cortical tissue lysate and 22C11 and 6E10 antibodies. Representative immunoblot and densitometric quantification was performed using different APP/PS1 mice. n = 4 mice per group were analyzed for statistical significance using one-way ANOVA followed by Newman–Keuls post hoc test. b ELISA performed to quantify Aβ_1–40 and Aβ_1–42 levels in the brain using Tris–HCl soluble fractions of cortical tissue. c Immunohistochemistry (pan-Aβ) and immunofluorescence (Thioflavin-S) performed to determine the area occupied by the insoluble Aβ plaque in the cortex and hippocampal brain regions. Representative images showing amyloid plaque DAB and Thioflavin-S staining in different brain regions. Percentage occupied area quantified using Cavalieri estimator probe of Stereo Investigator system (MBF Bioscience). Scale bar = 100 µm. n = 6 mice per group were analyzed. Statistical differences between groups determined using one-way ANOVA followed by Newman–Keuls post hoc test. *p < 0.05, **p < 0.01

Fig. 7

Aβ-Th1 and Aβ-Th17 cells activate microglia in APP/PS1 mice. a Immunohistochemistry performed to quantify number of reactive Iba1+ microglia cells in cortex and hippocampus brain regions. Representative pictures showing Iba1-reactive cells in different brain regions. Scale bar = 100 µm. Area with most Iba1-reactive cells highlighted by inserts for the cortex and hippocampus. Microglia morphology shown in higher magnification images. Scale bar = 20 µm. b Number of Iba1+-reactive microglia cells were quantified using optical fractionator module of Stereo Investigator system (MBF Bioscience). n = 5 mice per group were analyzed. c Western blot analysis performed to determine expression of iNOS and arginase-1 using cortical tissue lysate for assessment of microglial phenotypes. Representative immunoblot and densitometric quantification were performed using n = 4 mice per group. Statistical significance between different experimental groups determined using one-way ANOVA followed by Newman–Keuls post hoc test. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001

Fig. 8

Aβ-Th1 and Aβ-Th17 cells affect neurogenesis and synaptic plasticity in APP/PS1 mice. a Neuronal progenitor cell density determined by immunohistochemical staining of doublecortin positive (Dcx+) cells in the dentate gyrus region of the hippocampus. Representative images showing Dcx+ cells. Scale bar = 20 µm. Dcx+ cells were quantified using the optical fractionator module of Stereo Investigator system (MBF Bioscience). n = 6 mice per group were analyzed. b Western blot analyses performed to determine expression of presynaptic (synaptophysin) and postsynaptic (PSD95) neurons using cortical tissue protein. Representative immunoblot and densitometric quantification performed for n = 4 mice per group. Statistical significance between groups determined using one-way ANOVA followed by Newman–Keuls post hoc test. *p < 0.05, ****p < 0.0001