Share

January 2022; 9 (1) ArticleOpen Access

CSF-Derived CD4+ T-Cell Diversity Is Reduced in Patients With Alzheimer Clinical Syndrome

Chaitanya Joshi, Karthigayini Sivaprakasam, Scott Christley, Sara Ireland, Jacqueline Rivas, Wei Zhang, Danielle Sader, Rebecca Logan, Doris Lambracht-Washington, Roger Rosenberg, Munro Cullum, Brian Hitt, Quan-Zhen Li, Robert Barber, Benjamin Greenberg, Lindsay Cowell, Rong Zhang, Ann Stowe, Ryan Huebinger, Brendan Kelley, Nancy Monson
First published November 30, 2021, DOI: https://doi.org/10.1212/NXI.0000000000001106
Full PDF
Citation
Permissions

Make Comment

See Comments

Downloads
446

Share

Abstract

Background and Objectives Patients with Alzheimer dementia display evidence of amyloid-related neurodegeneration. Our focus was to determine whether such patients also display evidence of a disease-targeting adaptive immune response mediated by CD4+ T cells. To test this hypothesis, we evaluated the CSF immune profiles of patients with Alzheimer clinical syndrome (ACS), who display clinically defined dementia.

Methods Innate and adaptive immune profiles of patients with ACS were measured using multicolor flow cytometry. CSF-derived CD4+ and CD8+ T-cell receptor repertoire genetics were measured using next-generation sequencing. Brain-specific autoantibody signatures of CSF-derived antibody pools were measured using array technology or ELISA. CSF from similar-age healthy controls (HCs) was used as a comparator cohort.

Results Innate cells were expanded in the CSF of patients with ACS in comparison to HCs, and innate cell expansion increased with age in the patients with ACS, but not HCs. Despite innate cell expansion in the CSF, the frequency of total CD4+ T cells reduced with age in the patients with ACS. T-cell receptor repertoire genetics indicated that T-cell clonal expansion is enhanced, and diversity is reduced in the patients with ACS compared with similar-age HCs.

Discussion Examination of CSF indicates that CD4+ T cell–mediated adaptive immune responses are altered in patients with ACS. Understanding the underlying mechanisms affecting adaptive immunity will help move us toward the goal of slowing cognitive decline.

Glossary

ACS=
Alzheimer clinical syndrome;
AD=
Alzheimer disease;
ADL=
activities of daily living;
Aβ=
β-amyloid;
aMCI=
amnestic mild cognitive impairment;
ATI=
Aβ42/total tau (hTau) index;
CDR=
clinical dementia rating;
HC=
health control;
MS=
multiple sclerosis;
NfL=
neurofilament light;
TCRB=
T-cell receptor beta;
UTSW=
UT Southwestern Medical Center

The World Alzheimer Report estimates that the cost of dementia care will reach 2 trillion dollars by 2030, and dementia will affect nearly 75 million people.1 Alzheimer disease (AD) remains the most common dementia diagnosis,2 in which accumulation of β-amyloid (Aβ) plaques and hyperphosphorylated tau tangles in the brain is thought to cause neuronal loss and cognitive dysfunction.3 According to recent guidelines, a biological diagnosis of AD is verified using a classification system that encompasses both biofluid CSF levels of Aβ and tau and imaging approaches that measure neurodegeneration.4 Despite advances in diagnostic methods, effective therapies for AD remain unrealized.

In an effort to develop treatments for AD, emerging studies must endeavor to delineate underlying disease mechanisms, including the role of neuroinflammation in pathologic progression.5,-,8 Inflammation is mediated by both nonspecific innate and highly specific adaptive immune system components. A typical immune response to an infection, for example, would begin by activating innate immune components to sequester the infectious agent and present components of the infectious agent (antigens) to the cellular components of the adaptive immune system (T cells and B cells). Specific targeting of the infectious agent and its removal from the body are mediated initially by helper CD4+ T cells, which undergo activation, proliferation, and clonal expansion on exposure to the antigen presented by innate cells. In turn, helper CD4+ T cells produce cytokines and chemokines that activate cytotoxic CD8+ T cells to destroy the infectious agent and stimulate CD27+ memory B cells to develop into antibody-producing B cells that neutralize the infectious agent. This cascade of the immune response is essential to clearance of an infection. In the setting of AD pathology, there is some evidence that components of both the innate and adaptive immune systems are involved. For example, macrophages and neutrophils have been found in the brains of patients with AD,9 and both CD4+ and CD8+ T cells are frequently found at the sites of amyloid deposition in the brain.10,-,13 Yet, the role of innate and/or adaptive immune system components in the propagation of neuroinflammatory, regulatory, or even neuroprotective mechanisms remains largely unknown.14,-,16 Thus, elucidating the role of the immune system in the development of AD pathology and other dementias is critical to facilitate the development of therapeutics designed to prevent or slow cognitive decline.5,6

Our laboratory previously focused on examining early immune profile discordance in patients who have cognitive impairment, but are not experiencing clinical dementia to the extent that their activities of daily living (ADLs) are affected.17,-,19 Such patients are diagnosed with amnestic mild cognitive impairment (aMCI) with an anticipated conversion rate to AD diagnosis of 10% annually.20 Our previous goal was to determine whether early clinical manifestations of CNS inflammation could be demonstrated in the CSF of patients with aMCI. We investigated CSF-derived immune profiles of patients with aMCI and observed that they have elevated CNS inflammation as measured by a similar frequency and absolute number of CD45+ leukocytes compared with patients with multiple sclerosis (MS), a well-known CNS inflammatory disease driven by CD4+ T cells.17 However, the frequency of total CD4+ T cells was reduced in patients with aMCI compared with patients with MS despite evidence of Aβ deposition in the CNS of the patients with aMCI by PET imaging.19 Furthermore, the aMCI cohort demonstrated that as Aβ deposition in the brain increased, the frequency of CD4+ T cells in the CSF declined with significant correlation.18 These findings suggested that despite evidence of CNS damage, elevated adaptive immune responses mediated by CD4+ T cells were not occurring in patients with aMCI. Of interest, the frequency of innate immune cells was increased in the aMCI cohort in comparison to patients with MS, but did not result in expansion of CD4+ T cells in the CSF of the patients with aMCI.

We first hypothesized that perhaps CNS damage in patients with aMCI has not advanced (either in severity or duration) to incite a detectable disease-driven adaptive immune response. This could be the case as patients with aMCI do not exhibit deficits in cognition severe enough to affect their ADLs. On the other hand, patients diagnosed with Alzheimer clinical syndrome (ACS) who display deficits in cognition severe enough to affect ADLs are further along in their disease course. Thus, in an effort to understand the role of adaptive and innate immune populations, we immunophenotyped CSF-derived cells from patients with ACS with clinically confirmed deficits in ADLs. We used flow cytometry, T-cell receptor repertoire genetics, and brain-specific autoantibody signatures to define the innate and adaptive immune profile of patients with ACS compared with similar-age healthy controls (HCs).

Methods

Patient Recruitment

All subjects and/or their legally authorized study partners signed the written informed consent approved by the Institutional Review Board of the UT Southwestern Medical Center (UTSW), in accordance with the Federal Wide Assurance on file with the Department of Health and Human Services (USA).

The cohort (Table 1) consisted of 26 patients diagnosed with ACS (mean age 69.2 ± 9.0 years) and 12 similar-age HCs (mean age 70.0 ± 8.6 years). Standard clinical evaluations were performed on all participants at the UTSW Alzheimer's Disease Center or Memory Clinic. Clinical diagnoses were based on standard National Institute on Aging and Alzheimer's Association criteria for ACS using a multidisciplinary diagnostic conference format based on history, neurologic examination, clinical dementia rating (CDR) interview, and neuropsychological evaluation in accordance with National Alzheimer's Coordinating Center procedures used in National Institute on Aging-funded Alzheimer's Disease Research Centers.4 Of the 26 patients with ACS, 17 (identified by black squares in all figures) were confirmed for Alzheimer pathology using the Aβ42/total tau (hTau) index (ATI) and phosphorylated tau 181 (pTau181) tests in a commercial CLIA-certified laboratory. The remaining 9 cases that were not confirmed for Alzheimer pathology using ATI and pTau181 tests in a commercial CLIA-certified laboratory are identified by gray squares in all figures. In our research laboratory, we tested these 9 subjects for Aβ42, hTau, and pTau181 in the CSF with expected cohort comparison results indicative of increased amyloid burden and tau tangles in the brain (Table 1).21,22 In addition, we also measured neurofilament light (NfL) levels in the research laboratory as another indicator of neurodegeneration.23 Subjects were excluded if they did not display deficits in cognition severe enough to affect their ADLs and had a history of stroke, major medical and psychiatric disorders, unstable heart disease, uncontrolled hypertension, diabetes mellitus, or chronic inflammatory diseases. Limited availability of CSF restricted the number of samples used for each assay.

View this table:
Table 1

Cohort Summary

CSF and Blood Collection, Processing, and Flow Cytometry

CSF collected by lumbar puncture and blood from all subjects in the cohort were processed as previously published.17 Peripheral blood and CSF cells collected from the same subjects on the same day were stained in parallel using standard protocols established in the Monson laboratory.24 The sample gating strategy (eFigure 1A, links.lww.com/NXI/A656) and subtype frequencies (eFigure 1B) were based on our previous approach.17 Of the 26 patients with ACS, 21 were analyzed by flow cytometry to obtain frequencies of innate, CD4+ T-cell, CD8+ T-cell, CD19+ B-cell, and B-cell subsets. An additional 5 patients with ACS were analyzed by flow cytometry to obtain frequencies of innate cell subsets. Of note, the time from sample acquisition to initiation of processing was longer with samples that were not CLIA tested (gray squares in all figures) compared with those that were CLIA tested (black squares in all figures).

Detection of Analytes in CSF

ELISA kits for Aβ1-42, hTau, pTau181 (Innotest, Fujirebio, Malvern, PA), and NfL (Uman Diagnostics, Sweden) were used according to the manufacturer's instructions. The lowest limit of detection for each analyte was as follows: Aβ1-42 65 pg/mL, hTau 34 pg/mL, pTau(181) 13 pg/mL, and NfL 13 pg/mL. Samples below the detection limit were excluded from analysis.

TCR Next-Generation Sequencing

Genomic DNA (gDNA) was isolated from sorted CSF-derived CD4+ and CD8+ T cells and subjected to PCR using T-cell receptor beta (TCRB) gene rearrangement primer sets (eTable 1, links.lww.com/NXI/A661) previously published by others.25 Barcoded libraries were pooled and loaded onto an Illumina MiSeq instrument.

Repertoire Analysis

The TCR repertoire sequencing data were analyzed on VDJServer v1.1.226 and supporting software as detailed in the Supplemental Materials. The raw sequencing data are available at SRA (BioProject: PRJNA625786), and the raw sequencing data, postprocessed rearrangements, and analysis results are available at VDJServer (UUID: 887088384323808790-242ac116-0001-012). TCRB variable gene distributions are provided in eFigure 2, links.lww.com/NXI/A657. T-cell receptor sequences with the same V gene call, J gene call, and CDR3 sequence were determined to be derived from clonally related T cells for purposes of the clonal abundance and diversity.

Detection of Antibodies Against Aβ42

This assay was performed as previously published27 with modifications as detailed in the Supplementary Materials.

Brain Antigen Array

The brain antigen array consists of 63 brain-specific antigens (eTable 2, links.lww.com/NXI/A661). Samples were incubated with the arrays for 1 hour with agitation at room temperature, and Cy3-labeled anti-human IgG and Cy5-labeled anti-human IgM were used for detection at 1:1000 dilutions. Images were generated using the GenePix 4000B scanner and analyzed using GenePix Pro 7.0 software (Molecular Devices). The antibody score (Ab score) is detailed in eTable 3.

Data Analysis

All flow cytometry data were analyzed using FlowJo software (Treestar). The absolute cell numbers were calculated based on the FlowJo data and the hemocytometer counts. All data are presented as mean ± SEM. We used GraphPad Prism 8.0 for data analysis unless otherwise specified. All data were first tested for normal distribution using the Shapiro-Wilk test. Data sets passing the Shapiro-Wilk test were then analyzed using the unpaired, 2-sided Student t test (parametric). Data sets that did not pass Shapiro-Wilk test were Figure 1B (HC and ACS), 3A (ACS for total CD19), 3B (HC and ACS), 3C (ACS), 3D (ACS), and eFigures 3C, links.lww.com/NXI/A658 (ACS), 5A (HC), 5B (HC and ACS), and 5C (ACS). In these cases, the comparison was made using the nonparametric Mann-Whitney test. All correlation analyses were obtained by simple linear regression analysis in Prism. The brain antigen array data were analyzed with RStudio version 1.1.4, using the Wilcoxon test 2-sided hypothesis. A p value of less than 0.05 was considered statistically significant.

Figure 1
Figure 1 Innate Cells in the CSF Are Expanded and Positively Correlate With Age in Patients With ACS

(A) The frequency (%) of innate cells in the CSF of 21 patients with ACS was compared with 12 similar-age healthy controls (HCs). (B) Correlation of CSF-derived innate cell frequency with age in the ACS cohort. (C) The relative frequencies of innate cell subtypes in the CSF of an ACS subcohort. CD45+ leukocytes that did not express any other lineage markers in the panel were categorized as other leukocytes. The mean ± SEM of each group is provided in panels A and C. Circles indicate HC donors, solid black squares represent CLIA-tested patients with ACS, and solid gray squares represent non–CLIA-tested patients with ACS. ACS = Alzheimer clinical syndrome. *p < 0.05.

Data Availability

Anonymized data will be shared by request from any qualified investigator.

Results

Innate Cell Expansion and Correlation With Age

We hypothesized that features of the immune response would be affected in patients with ACS who display deficits in cognition severe enough to affect ADLs. To begin addressing this hypothesis, we used multiparameter flow cytometry to identify innate cells and adaptive (i.e., CD4+ and CD8+ T cells and B cells) leukocyte subtypes in the CSF and blood of 21 patients with ACS and 12 similar-age HCs. We also identified innate cell subsets in the CSF of 5 additional patients with ACS by multiparameter flow cytometry. Patients with ACS in this cohort demonstrated expansion of general innate cell populations in the CSF compared with similar-age HCs by frequency (Figure 1A, p < 0.05), but not absolute number (eFigure 3A, links.lww.com/NXI/A658). In addition, the frequency of innate cells in the CSF increased with age in the ACS patients (Figure 1B, p = 0.03, r2 = 0.22), but not in the similar-age HCs (data not shown). Of note, the frequency (eFigure 3B) and absolute number (eFigure 3C) of CD45+ leukocytes in the CSF were similar in both cohorts. In some cases, the absolute number of CD45+ leukocytes in both the ACS and HC cohorts was nearly undetectable, whereas others reached very high levels. The innate cell subtype in the CSF of patients with ACS consisted mostly of CD14+ monocytes (Figure 1C). The frequency of CD45+ leukocytes in the blood was also similar in both cohorts (eFigure 3D), as was the frequency of innate cells in the blood (eFigure 3E). Finally, in contrast to the frequency of innate cells in the CSF, the frequency of innate cells in the blood does not correlate with age in the ACS patients (eFigure 3F). The 11-color panel that allows us to segregate the innate cell subtypes was used on only 5 of the patients with ACS (Figure 1C), and so a more detailed analysis of the innate cell subtypes affecting the frequency and correlation with age could not be performed. Similar-age HCs did not display correlation of age with innate cell frequency in the blood (data not shown).

CSF-Derived T-Cell Features

Next, we focused on T cells, which are a component of the adaptive immune system that we anticipated would be responsive to the expansion of innate cells and the elevation of neurodegeneration in the patients with ACS as evidenced by changes in the CSF of Aβ42, hTau, pTau181, and NfL (Table 1). The CD4+ T-cell frequency (Figure 2A) and absolute number (data not shown) in the CSF were similar in both cohorts. Nevertheless, the frequency of CD4+ T cells in the CSF negatively correlated with age in the ACS patients (p < 0.005, r2 = 0.35; Figure 2B), but did not correlate in the similar-age HCs (data not shown). The frequency of CD4+ T cells also did not correlate with the MMSE score or other clinical measures that were available, including markers of AD pathology (i.e., Aβ42) or general neurodegeneration (i.e., NfL).

Figure 2
Figure 2 CD4+ T Cells in the CSF Negatively Correlate With Age and Display Reduced Diversity Index in Patients With ACS

(A) The frequency of CD4+ T cells in the CSF of 21 patients with ACS was compared with 12 similar-age healthy controls (HCs). (B) Correlation of CSF-derived CD4+ T-cell frequency with age of the ACS cohort. (C) TCRB diversity indices for CD4+ T cells in the ACS population as compared to HCs. (D) TCRB diversity differences for CD8+ T cells in the ACS population as compared to HCs. The mean ± SEM of each group is provided below each column of panels A, C, and D. Circles indicate HC donors, solid black squares represent CLIA-tested patients with ACS, and solid gray squares represent non–CLIA-tested patients with ACS. ACS = Alzheimer clinical syndrome; TCRB = T-cell receptor beta.

Next, we analyzed the extent of clonal expansion within the TCRB gene repertoires expressed by CSF-derived CD4+ and CD8+ T cells. The frequency of unactivated T cells by TCRB sequence analysis (“NONE”; eFigure 4C, links.lww.com/NXI/A659) and clonally expanded CD4+ T cells of moderate range by TCRB sequence analysis (eFigure 4D) was reduced in the CSF-derived CD4+ T-cell population of the patients with ACS compared with similar-age HCs. In contrast, the frequency of advanced clonally expanded T cells by TCRB sequence analysis (greater than 1% representation in the TCRB sequence repertoire) was significantly higher in the CSF-derived CD4+ T-cell population TCRB sequence repertoire of the patients wtih ACS compared with the similar-age HCs (61% vs <20%, p < 0.01) (eFigure 4E). In parallel, the frequency of CD8+ T cells in the patients with ACS was comparable to similar-age HCs (eFigure 4A) and did not correlate with age (eFigure 4B). Furthermore, CSF-derived CD8+ T cells of patients with ACS displayed similar representation of all 3 categories of clonally expanded CD8+ T cells (eFigure 4F–H) compared with similar-age HCs. T-cell subset clonal expansion in the blood was not examined because the frequency of CD4+ and CD8+ T cells in the blood was similar in both cohorts, and there was no correlation with age in patients with ACS (data not shown).

In addition to specifically analyzing clonal expansion of the CSF repertoires, we also analyzed repertoire diversity by calculating Hill numbers over a range of q values.28 We used Alakazam,29 which is implemented in VDJServer and uses resampling techniques to account for sample-to-sample variability in sequence numbers. Hill numbers quantify repertoire diversity as a function of both clonal expansion (the relative clonal abundances across all clones) and the overall number of distinct clones in a repertoire. A high diversity index indicates that the repertoire gene distribution has a large number of clones with relatively uniform abundances, as would be the case for repertoires dominated by unactivated or naive T cells. Once a T-cell population responds to its cognate antigen, it becomes activated and undergoes clonal expansion. Subsequently, clonal expansion results in a reduction of diversity within the repertoire, resulting in a low diversity index when T cells are undergoing clonal expansion. CSF-derived CD4+ T cells of the patients with ACS displayed a reduced diversity index within the expressed TCRB repertoires (Figure 2C). In contrast, the CSF-derived CD4+ T cells of the similar-age HCs exhibited higher diversity as expected for a T-cell population dominated by a large number of non-expanded clones (2,567 vs 9,107, p < 0.001). CSF-derived CD8+ T-cell diversity index was similar between the patients with ACS and similar-age HC cohorts (Figure 2D) as a reflection of similar frequencies of advanced CD8+ T-cell clones.

Humoral Immune Response Features

Activated CD4+ T cells are critical in facilitating B-cell activation and class switching,30 and the CD4+ T cells in the CSF of patients with ACS displayed genetic markers of activation including clonal expansion and, in this case, subsequent reduced diversity. Thus, we next examined the impact of this T-cell dynamic on B-cell subsets. The frequency of total B cells (Figure 3A) and the naive (Figure 3B) and memory (Figure 3C) B-cell subtypes was comparable in both cohorts. Naive B cells were not detected in the CSF of 2 patients with ACS and 1 HC. CD138+ antibody–producing B cells were detected in the CSF of both patients with ACS and HCs at similar frequencies (Figure 3D), whereas an earlier study focused on patients with mild AD could not detect any CD138+ antibody–producing B cells.31 Both naive and CD138+ antibody–producing B-cell frequencies were affected by the covariate of sample handling as noted in the methods. Total IgM and IgG concentrations in the CSF were also similar (data not shown). Of interest, despite the reduction of Aβ42 in the patients with ACS compared with similar-age HCs (Table 1), we did not observe a complimentary increase in titers of anti-Aβ42 of either the IgM or IgG isotype (eFigure 5A and B, links.lww.com/NXI/A660). In addition, the concentration of NfL in the CSF of patients with ACS is elevated in comparison to similar-age HCs (Table 1), yet titers of anti-NfL antibody of either isotype (eFigure 5C and D) were similar in both cohorts. Antibody reactivity to other brain antigens was also comparable in both cohorts (eTable 3, links.lww.com/NXI/A661).

Figure 3
Figure 3 B-Cell Subset Frequencies in the CSF Are Unaltered in Patients With ACS

The frequencies of (A) CD19+ B cells and subsets including (B) naive cells, (C) memory cells, and (D) antibody-producing B cells were comparable. The mean ± SEM of each group and number of samples (n) included are given below each column. Circles indicate HC donors, solid black squares represent CLIA-tested patients with ACS, and solid gray squares represent non–CLIA-tested patients with ACS. ACS = Alzheimer clinical syndrome; HC = healthy control.

Discussion

We hypothesized that neurodegeneration in patients with ACS must reach an advanced and critical stage to incite a notable adaptive immune response shift in comparison to similar-age HCs. Our findings indicated increased amyloid burden in the brain (as measured by detection of reduced Aβ42 in the CSF) and increased neuronal damage (as measured by detection of NfL in the CSF) in patients with ACS compared with similar-age HCs. We anticipated that advancing neurodegeneration in the brain would promote an increase in the absolute number of CD45+ leukocytes in the CSF of the patients with ACS. Instead, the absolute number of CD45+ leukocytes and each lymphocyte subset remained unchanged compared with similar-age HCs. The broad range of cell counts in the cohort as a whole likely accounted for this, and so comparisons using the frequencies of each CD45+ leukocyte subset (innate, CD4+ T cells, CD8+ T cells, and CD19+ B cells) were used to evaluate changes to the immune profile.

Indeed, the innate cell frequency was increased in the patients with ACS, just as we had observed in patients with aMCI in our earlier studies. Thus, cognitive decline that affects ADLs is not a necessary driver of innate cell expansion. It is possible that innate cell subtypes are affected differently, particularly as disease progresses. However, the flow cytometry panel we used to segregate the innate cell subtypes was only used on 5 of the subjects (Figure 1C), and so a more detailed analysis of the innate cell subtypes affecting the frequency or correlation with age or neurodegenerative markers such as NfL was not performed for this study.

We anticipated that the frequency of CD4+ and CD8+ T cells would also be increased in patients with ACS because we had observed innate cell expansion, which would likely support T-cell activation and proliferation. In addition, others had found T cells in the postmortem AD brain,10,32 and both CD4+ and CD8+ T cells are present at the sites of amyloid deposition in AD brain tissue.10,33 However, it remains unknown whether their contribution is neurodegenerative, neuroprotective, or of no consequence. Others have shown that CD4+ and CD8+ T-cell frequencies in the CSF are similar in patients with dementia and aged controls.31 However, the cohort of patients with dementia in this earlier article excluded subjects that displayed severe cognitive decline, whereas the dementia cohort presented here focused on patients with dementia with cognitive decline severe enough to affect ADLs. Thus, we anticipated that the frequencies of CD4+ T cells in the CSF of patients with ACS would be increased in comparison to similar-age controls. Instead, patients with ACS did not display an increased frequency of CD4+ or CD8+ T cells in the CSF, indicating that cognitive decline severe enough to affect ADLs is not a sufficient trigger to observe increased CD4+ or CD8+ T-cell frequencies in the CSF. However, this degree of cognitive decline may be sufficient to retain a portion of CD4+ T cells within brain tissue as the frequency of CD4+ T cells in the CSF decreased with advancing age of disease.

Similar frequencies of T cells do not preclude that the underlying T-cell repertoire is also unchanged. To investigate this, we used TCR repertoire clonality and diversity index to measure CD4+ and CD8+ T-cell activation status in the CSF of patients with ACS and similar-age HCs. We found significantly increased clonal expansion in CD4+ T cells within the CSF of patients with ACS compared with controls, which was further verified by substantially reduced diversity index. However, CSF-derived CD8+ T cells displayed similar clonal representation and diversity index in patients with ACS compared with similar-age HCs. Earlier studies suggested a lack of antigen-triggered clonal expansion of T cells found in postmortem brain tissue of patients with AD,34 but our observations of T cells within the CSF suggest that clonal expansion and reduced diversity index of CD4+ T cells are readily identified in patients with ACS. Enhanced clonal expansion of CD8+ T cells may not be evident in the CSF because activated, proliferating and clonally expanding CD8+ T cells are retained within the brain tissue where amyloid and tau depositions reside. CD4+ T cells may migrate more freely between the periphery and brain tissue, which would facilitate detection of clonally expanded CD4+ T cells in the CSF. Of note, an earlier study demonstrating that CD8+ T cells from the CSF of a mixed cohort of patients with MCI and AD demonstrate enhanced clonal expansion compared with HCs.35 However, there were several methodological distinctions between the 2 studies that likely accounts for this contrast including the use of overnight freeze-thawed CSF cells vs fresh collections, limited availability of cells in the RNAseq platforms instead of total T-cell subset library generation, and lack of diversity calculations to delineate the nature of the clonally expanded population. Further studies are needed to understand the impact of CSF-derived and brain-derived clonally expanding CD4+ and CD8+ T cells in the pathology of AD, keeping in mind that their involvement in different processes of AD pathology may be affected by the TCRB genes they express.

Naive30 and memory36 B cells require CD4+ T-cell help to become activated in response to soluble antigen and differentiate to efficient antibody-producing cells. Because CD4+ T-cell frequencies were reducing with age of the patients with ACS, we expected that the subtype distribution within the B-cell population of the CSF would be similar among the cohorts or that representation of activated antibody-producing B cells would even be reduced in the patients with ACS. Indeed, the B-cell subtype distributions in the CSF were the same in both cohorts, supporting the concept that CD4+ T-cell help is inadequate to elicit activation and expansion of B cells in patients with ACS. One caveat to this conclusion is that there is a sample handling covariate in the data set, which appears to affect B-cell subsets in particular. This limitation to the data set emphasizes that care must be taken when procuring data sets from multiple clinics or institutions to ensure that the time from sample acquisition to sample processing is comparable, particularly if B-cell subset frequency data are a primary focus of the investigations.

A second caveat to the conclusion that CD4+ T-cell help is inadequate to elicit activation and expansion of B cells in patients with ACS is that B-cell activation may be occurring within the CNS tissue itself,37 which is not measurable in a living patient cohort. In addition, it is possible that the frequency of B cells reactive to amyloid or tau is specifically upregulated. We did not test this in our CSF cohort, but others have observed an increase in anti-Aβ42 antibody–secreting B cells in the periphery compared with controls.38 In support of our findings regarding the B-cell compartment similarities in the CSF, we also did not observe higher concentrations of total antibody or specifically anti-Aβ42 or anti-NfL antibodies in the CSF of patients with ACS compared with HCs. Others have demonstrated that patients with probable AD have a 31% decrease in the titer of anti-Aβ antibody in the CSF compared with controls.39 Increased titers of disease-specific antibodies would likely require robust CD4+ T-cell help to facilitate B-cell expansion and differentiation to antibody secreting cells. Thus, the lack of increased titers of anti-Aβ antibody in the CSF of this ACS patient cohort is further evidence of limited T-cell activation that may be specific to amyloid reactive T cells matriculating the CSF.

We had anticipated that advancing neurodegeneration in the ACS population would elicit a robust adaptive immune response in patients with ACS that was discordant from similar-age HCs based on the understanding that a diagnosis of ACS includes cognitive deficits that affect ADLs. Instead, despite the robust presence of biomarkers indicative of CNS damage and expansion of innate cells by frequency in the CSF of patients with ACS compared with similar-age HCs, T-cell clonal expansion and the diversity index were suppressed and antibody titers against Aβ42 remained similar. These preliminary observations in a limited research cohort further support the continued exploration of potential therapeutic approaches to boost the specific adaptive immune response while limiting off-target effects.40,-,42 In light of the finding that only approximately 20% of participants in an initial clinical vaccine trial (AN1792) showed the desired antibody response,43 future immune-mediated therapeutic approaches would benefit from a better understanding of adaptive immune responses that provide protection from neurodegeneration. Furthermore, the reduced diversity index in the CSF-derived CD4+ T cells of patients with ACS in comparison to similar-age HCs may provide a unique and effective biomarker for early diagnosis of ACS and provide an avenue to identify those patients with dementia who will advance to develop AD pathology. For example, 1 subject (69M) had an MMSE of 29, but a diversity index that was 7.6× lower than the average in the similar-age HCs. This subject was diagnosed with ACS based on cognitive deficits that affected his ADLs, but this very low-diversity index places this subject within the ACS cohort independently. Further studies are warranted to understand whether the immune profile changes we presented here contribute directly to progression of AD pathology.

Study Funding

National Institute of Neurological Disorders and Stroke awards R21 NS104509 and R01 NS102417 to NM supported this work. This project was also supported by the Texas Alzheimer's Research and Care Consortium (TARCC) as awarded to RH and NM.

Disclosure

There are no relevant disclosures for the authors. Go to Neurology.org/NN for full disclosures.

Acknowledgment

The authors thank the patients in the study and their families for their participation. The authors appreciate the support of Moody Foundation Flow Core, Microarray Core, and O'Donnell Brain Institute Biorepository Core facilities staff at UTSW for their assistance in data acquisition. They thank all the clinical staff at Alzheimer's Disease Center and Memory Clinic at UTSW for their assistance in sample acquisition and transport.

Appendix Authors

Table

Footnotes

  • Go to Neurology.org/NN for full disclosures. Funding information is provided at the end of the article.

  • The Article Processing Charge was funded by the authors.

  • Received April 16, 2021.
  • Accepted in final form September 14, 2021.

This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND), which permits downloading and sharing the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.

References

  1. 1.↵
    1. Prince MJ,
    2. Wimo A,
    3. Guerchet M,
    4. Ali GC,
    5. Wu Y-T,
    6. Prina M
    . World Alzheimer Report 2015: The Global Impact of Dementia: An Analysis of Prevalence, Incidence, Cost and Trends. Vol 2017. Alzheimer's Disease International. 2015.
  2. 2.↵
    Alzheimer's A. Alzheimer's disease facts and figures. Alzheimers Dement. 2016;12(4):459-509.
    OpenUrlCrossRefPubMed
  3. 3.↵
    1. Calsolaro V,
    2. Edison P
    . Neuroinflammation in Alzheimer's disease: current evidence and future directions. Alzheimers Dement. 2016;12(6):719-732.
    OpenUrl
  4. 4.↵
    1. Jack CR Jr.,
    2. Bennett DA,
    3. Blennow K, et al.
    NIA‐AA research framework: toward a biological definition of Alzheimer's disease. Alzheimer's Demen. 2018;14(4):535-562.
    OpenUrl
  5. 5.↵
    1. Heppner FL,
    2. Ransohoff RM,
    3. Becher B
    . Immune attack: the role of inflammation in Alzheimer disease. Nat Rev Neurosci. 2015;16(6):358-372.
    OpenUrlCrossRefPubMed
  6. 6.↵
    1. Heneka MT,
    2. Carson MJ,
    3. El Khoury J, et al
    . Neuroinflammation in Alzheimer's disease. Lancet Neurol. 2015;14(4):388-405.
    OpenUrlCrossRefPubMed
  7. 7.↵
    1. Sweeney MD,
    2. Sagare AP,
    3. Zlokovic BV
    . Blood-brain barrier breakdown in Alzheimer disease and other neurodegenerative disorders. Nat Rev Neurol. 2018;14(3):133.
    OpenUrlPubMed
  8. 8.↵
    1. Arranz AM,
    2. De Strooper B
    . The role of astroglia in Alzheimer's disease: pathophysiology and clinical implications. Lancet Neurol. 2019;18(4):406-414.
    OpenUrlCrossRef
  9. 9.↵
    1. Fiala M,
    2. Cribbs DH,
    3. Rosenthal M,
    4. Bernard G
    . Phagocytosis of amyloid-β and inflammation: two faces of innate immunity in Alzheimer's disease. J Alzheimer's Dis. 2007;11(4):457-463.
    OpenUrlCrossRefPubMed
  10. 10.↵
    1. Rogers J,
    2. Luber-Narod J,
    3. Styren SD,
    4. Civin WH
    . Expression of immune system-associated antigens by cells of the human central nervous system: relationship to the pathology of Alzheimer's disease. Neurobiol Aging. 1988;9(4):339-349.
    OpenUrlCrossRefPubMed
  11. 11.↵
    1. Rogers J,
    2. Mufson EJ
    . Demonstrating immune-related antigens in Alzheimer's disease brain tissue. Neurobiol Aging. 1990;11(4):477-479.
    OpenUrlPubMed
  12. 12.↵
    1. Itagaki S,
    2. McGeer PL,
    3. Akiyama H
    . Presence of T-cytotoxic suppressor and leucocyte common antigen positive cells in Alzheimer's disease brain tissue. Neurosci Lett. 1988;91(3):259-264.
    OpenUrlCrossRefPubMed
  13. 13.↵
    1. Merlini M,
    2. Kirabali T,
    3. Kulic L,
    4. Nitsch RM,
    5. Ferretti MT
    . Extravascular CD3+ T cells in brains of Alzheimer disease patients correlate with tau but not with amyloid pathology: an immunohistochemical study. Neurodegener Dis. 2018;18(1):49-56.
    OpenUrlCrossRef
  14. 14.↵
    1. Dong Y,
    2. Lagarde J,
    3. Xicota L, et al
    . Neutrophil hyperactivation correlates with Alzheimer's disease progression. Ann Neurol. 2018;83(2):387-405.
    OpenUrlCrossRef
  15. 15.↵
    1. Pellicanò M,
    2. Larbi A,
    3. Goldeck D, et al
    . Immune profiling of Alzheimer patients. J Neuroimmunol. 2012;242(1-2):52-59.
    OpenUrlCrossRefPubMed
  16. 16.↵
    1. Jevtic S,
    2. Sengar AS,
    3. Salter MW,
    4. McLaurin J
    . The role of the immune system in Alzheimer disease: etiology and treatment. Ageing Res Rev. 2017;40:84-94.
    OpenUrlCrossRef
  17. 17.↵
    1. Monson NL,
    2. Ireland SJ,
    3. Ligocki AJ, et al
    . Elevated CNS inflammation in patients with preclinical Alzheimer's disease. J Cereb Blood Flow Metab. 2014;34(1):30-33.
    OpenUrlCrossRefPubMed
  18. 18.↵
    1. Tarumi T,
    2. Harris TS,
    3. Hill C, et al
    . Amyloid burden and sleep blood pressure in amnestic mild cognitive impairment. Neurology. 2015;85(22):1922-1929.
    OpenUrlPubMed
  19. 19.↵
    1. Stowe AM,
    2. Ireland SJ,
    3. Ortega SB, et al.
    Adaptive lymphocyte profiles correlate to brain Abeta burden in patients with mild cognitive impairment. J Neuroinflammation. 2017;14(1):149.
    OpenUrl
  20. 20.↵
    1. Michaud TL,
    2. Su D,
    3. Siahpush M,
    4. Murman DL
    . The risk of incident mild cognitive impairment and progression to dementia considering mild cognitive impairment subtypes. Dement Geriatr Cogn Dis Extra. 2017;7(1):15-29.
    OpenUrlCrossRefPubMed
  21. 21.↵
    1. Fagan AM,
    2. Roe CM,
    3. Xiong C,
    4. Mintun MA,
    5. Morris JC,
    6. Holtzman DM
    . Cerebrospinal fluid tau/beta-amyloid(42) ratio as a prediction of cognitive decline in nondemented older adults. Arch Neurol. 2007;64(3):343-349.
    OpenUrlCrossRefPubMed
  22. 22.↵
    1. Perrin RJ,
    2. Fagan AM,
    3. Holtzman DM
    . Multimodal techniques for diagnosis and prognosis of Alzheimer's disease. Nature. 2009;461(7266):916-922.
    OpenUrlCrossRefPubMed
  23. 23.↵
    1. Zetterberg H,
    2. Skillbäck T,
    3. Mattsson N, et al
    . Association of cerebrospinal fluid neurofilament light concentration with Alzheimer disease progression. JAMA Neurol. 2016;73(1):60-67.
    OpenUrl
  24. 24.↵
    1. Rivas JR,
    2. Ireland SJ,
    3. Chkheidze R, et al.
    Peripheral VH4+ plasmablasts demonstrate autoreactive B cell expansion toward brain antigens in early multiple sclerosis patients. Acta Neuropathol. 2017;133(1):43-60.
    OpenUrl
  25. 25.↵
    1. Scheinberg P,
    2. Melenhorst JJ,
    3. Hill BJ, et al.
    The clonal composition of human CD4+CD25+Foxp3+ cells determined by a comprehensive DNA-based multiplex PCR for TCRB gene rearrangements. J Immunol Methods. 2007;321(1-2):107-120.
    OpenUrlCrossRefPubMed
  26. 26.↵
    1. Christley S,
    2. Scarborough W,
    3. Salinas E, et al
    . VDJServer: a cloud-based analysis portal and data commons for immune repertoire sequences and rearrangements. Front Immunol. 2018;9(0):976.
    OpenUrlCrossRefPubMed
  27. 27.↵
    1. Lambracht-Washington D,
    2. Fu M,
    3. Frost P,
    4. Rosenberg RN
    . Evaluation of a DNA Aβ42 vaccine in adult rhesus monkeys (Macaca mulatta): antibody kinetics and immune profile after intradermal immunization with full-length DNA Aβ42 trimer. Alzheimer's Res Ther. 2017;9(1):30.
    OpenUrl
  28. 28.↵
    1. Hill M
    . Diversity and evenness: a unifying notation and its consequences. Ecology. 1973;54(0):427-432.
    OpenUrlCrossRef
  29. 29.↵
    1. Gupta NT,
    2. Vander Heiden JA,
    3. Uduman M,
    4. Gadala-Maria D,
    5. Yaari G,
    6. Kleinstein SH
    . Change-O: a toolkit for analyzing large-scale B cell immunoglobulin repertoire sequencing data. Bioinformatics. 2015;31(20):3356-3358.
    OpenUrlCrossRefPubMed
  30. 30.↵
    1. Abbas AK,
    2. Murphy KM,
    3. Sher A
    . Functional diversity of helper T lymphocytes. Nature. 1996;383(6603):787-793.
    OpenUrlCrossRefPubMed
  31. 31.↵
    1. Lueg G,
    2. Gross CC,
    3. Lohmann H, et al
    . Clinical relevance of specific T-cell activation in the blood and cerebrospinal fluid of patients with mild Alzheimer's disease. Neurobiol Aging. 2015;36(1):81-89.
    OpenUrlCrossRefPubMed
  32. 32.↵
    1. Parachikova A,
    2. Agadjanyan MG,
    3. Cribbs DH, et al
    . Inflammatory changes parallel the early stages of Alzheimer disease. Neurobiol Aging. 2007;28(12):1821-1833.
    OpenUrlCrossRefPubMed
  33. 33.↵
    1. Fiala M,
    2. Liu QN,
    3. Sayre J, et al
    . Cyclooxygenase-2-positive macrophages infiltrate the Alzheimer's disease brain and damage the blood-brain barrier. Eur J Clin Invest. 2002;32(5):360-371.
    OpenUrlCrossRefPubMed
  34. 34.↵
    1. Togo T,
    2. Akiyama H,
    3. Iseki E, et al
    . Occurrence of T cells in the brain of Alzheimer's disease and other neurological diseases. J Neuroimmunol. 2002;124(1-2):83-92.
    OpenUrlCrossRefPubMed
  35. 35.↵
    1. Gate D,
    2. Saligrama N,
    3. Leventhal O, et al
    . Clonally expanded CD8 T cells patrol the cerebrospinal fluid in Alzheimer's disease. Nature. 2020;577(7790):399-404.
    OpenUrlCrossRef
  36. 36.↵
    1. Duffy D,
    2. Yang CP,
    3. Heath A,
    4. Garside P,
    5. Bell EB
    . Naive T‐cell receptor transgenic T cells help memory B cells produce antibody. Immunology. 2006;119(3):376-384.
    OpenUrlCrossRefPubMed
  37. 37.↵
    1. Meinl E,
    2. Krumbholz M,
    3. Hohlfeld R
    . B lineage cells in the inflammatory central nervous system environment: migration, maintenance, local antibody production, and therapeutic modulation. Ann Neurol. 2006;59(6):880-892.
    OpenUrlCrossRefPubMed
  38. 38.↵
    1. Sollvander S,
    2. Ekholm-Pettersson F,
    3. Brundin RM, et al.
    Increased number of plasma B cells producing autoantibodies against Abeta42 protofibrils in Alzheimer's disease. J Alzheimers Dis. 2015;48(1):63-72.
    OpenUrl
  39. 39.↵
    1. Du Y,
    2. Dodel R,
    3. Hampel H, et al
    . Reduced levels of amyloid beta-peptide antibody in Alzheimer disease. Neurology. 2001;57(5):801-805.
    OpenUrlCrossRefPubMed
  40. 40.↵
    1. Lemere CA,
    2. Masliah E
    . Can Alzheimer disease be prevented by amyloid-β immunotherapy?. Nat Rev Neurol. 2010;6(2):108.
    OpenUrlCrossRefPubMed
  41. 41.↵
    1. Vandenberghe R,
    2. Riviere ME,
    3. Caputo A, et al
    . Active Aβ immunotherapy CAD106 in Alzheimer's disease: a phase 2b study. Alzheimers Dement (N Y). 2017;3(1):10-22.
    OpenUrl
  42. 42.↵
    1. Boxer AL,
    2. Qureshi I,
    3. Ahlijanian M, et al
    . Safety of the tau-directed monoclonal antibody BIIB092 in progressive supranuclear palsy: a randomised, placebo-controlled, multiple ascending dose phase 1b trial. Lancet Neurol. 2019;18(6):549-558.
    OpenUrl
  43. 43.↵
    1. Gilman S,
    2. Koller M,
    3. Black R, et al.
    Clinical effects of Aβ immunization (AN1792) in patients with AD in an interrupted trial. Neurology. 2005;64(9):1553-1562.
    OpenUrlCrossRefPubMed

Letters: Rapid online correspondence

No comments have been published for this article.
Comment

REQUIREMENTS

If you are uploading a letter concerning an article:
You must have updated your disclosures within six months: http://submit.neurology.org

Your co-authors must send a completed Publishing Agreement Form to Neurology Staff (not necessary for the lead/corresponding author as the form below will suffice) before you upload your comment.

If you are responding to a comment that was written about an article you originally authored:
You (and co-authors) do not need to fill out forms or check disclosures as author forms are still valid
and apply to letter.

Submission specifications:

  • Submissions must be < 200 words with < 5 references. Reference 1 must be the article on which you are commenting.
  • Submissions should not have more than 5 authors. (Exception: original author replies can include all original authors of the article)
  • Submit only on articles published within 6 months of issue date.
  • Do not be redundant. Read any comments already posted on the article prior to submission.
  • Submitted comments are subject to editing and editor review prior to posting.

More guidelines and information on Disputes & Debates

Compose Comment

More information about text formats

Plain text

  • No HTML tags allowed.
  • Web page addresses and e-mail addresses turn into links automatically.
  • Lines and paragraphs break automatically.
Author Information
NOTE: The first author must also be the corresponding author of the comment.
First or given name, e.g. 'Peter'.
Your last, or family, name, e.g. 'MacMoody'.
Your email address, e.g. higgs-boson@gmail.com
Your role and/or occupation, e.g. 'Orthopedic Surgeon'.
Your organization or institution (if applicable), e.g. 'Royal Free Hospital'.
Publishing Agreement
NOTE: All authors, besides the first/corresponding author, must complete a separate Publishing Agreement Form and provide via email to the editorial office before comments can be posted.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.

Vertical Tabs

You May Also be Interested in

Back to top

Related Articles

  • No related articles found.

Topics Discussed

Alert Me

Advertisement