An Altered Relationship between Soluble TREM2 and Inflammatory Markers in Young Adults with Down Syndrome: A Preliminary Report

In the last half of the 20th century, the life expectancy of individuals with Down syndrome (DS) has increased to 60 years (1–3), highlighting the importance of understanding age-related disease in this population (4). Most individuals with DS carry three full copies of chromosome 21. The amyloid precursor protein (APP) gene, located on chromosome 21, is processed into amyloid β (Aβ). The overabundance of Aβ resulting from three copies of APP leads to Aβ plaque deposition in ∼50% of people with DS over the age of 30 and subsequently increases their risk for dementia in middle age (around age 40) (5, 6). The study of early adulthood in DS potentially provides a unique model for the early biology of Alzheimer's disease (AD) in the general population.

Assessment of subtle cognitive changes is challenging in DS, partly because of the presence and variability of intellectual disability (7, 8). Therefore, defining biomarkers of dementia progression is critical in this population of individuals. AD neuropathology, amyloid, and tau accumulate early in DS, and plasma Aβ and tau represent potential biomarker candidates (9–11). In DS, the variable severity of Aβ deposition within age groups and age of onset of dementia suggest that factors other than the presence of triplication of the APP gene contribute to the timing and severity of amyloid deposition and therefore the onset of AD (5, 12–14).

Biomarkers of peripheral inflammation and the innate immune response are elevated in DS (15–18). Triggering receptor expressed in myeloid cells 2 (TREM2) is a pattern recognition receptor that can be activated by both pathogen- and danger-associated molecular patterns in the innate immune response (19, 20). Loss-of-function genetic variants in TREM2, located on chromosome 6, are risk factors for AD and other neurodegenerative diseases (21–23). Soluble TREM2 (sTREM2), a soluble cleavage product of TREM2, is elevated in AD cerebrospinal fluid and positively correlates with Aβ and cognitive decline (24–32). There is relatively little information about TREM2 in DS, although one group describes elevated TREM2 protein levels in young adults and declining levels with aging (33, 34).

The hypothesis of this investigation was that there is a relationship between sTREM2 and inflammatory markers in DS, prior to the development of dementia symptoms. We found that young adults with DS displayed an altered immune profile compared with neurotypical controls, with increased levels of sTREM2 and inflammatory markers in plasma. In young adults with DS, sTREM2 correlated positively with 24 of the 38 measured cytokines, whereas there were no significant correlations in the control group. In addition, sTREM2 clustered with different cytokines in the two groups. The results of this preliminary report implicate an altered relationship between sTREM2 and inflammatory markers in young adults with DS predementia.

Fifteen young adults with DS (mean age: 29.5 y, range: 26–34 y; five females) and 16 neurotypical age-matched controls (mean age: 29.6 y, range: 25–36 y; four females) were enrolled in the study under a protocol approved by the Cleveland Clinic Institutional Review Board. We have reviewed the medical histories of the participants and found that none have reported systemic inflammatory diseases or known infections at the time of enrollment. No participants reported use of nonsteroidal anti-inflammatory drugs, which could have impacted their cytokine profiles. For participants with DS, inclusion criteria included a medical diagnosis of DS, age of 25–35 y, and the ability to assent to participation and complete the study procedures. Participants were excluded for a history of major neurologic or psychiatric illness other than DS or documented symptoms of dementia. Participants with DS provided verbal or written informed assent, as appropriate, and their guardians provided written informed consent. Control participants provided written informed consent. Biospecimens were collected and processed through the Lou Ruvo Center for Brain Health Aging and Neurodegenerative Disease Biobank. Prior to additional study interventions, participants with DS underwent a comprehensive clinical assessment to minimize the chance of including participants that were showing subtle signs of dementia. This assessment was completed by a psychiatrist specializing in developmental disabilities and included a psychiatric diagnostic interview with participant and caregiver, medical history, and mental status examination (35). Participant caregivers also completed the Dementia Screening Questionnaire for Individuals with Intellectual Disabilities (36) and the Dementia Questionnaire for People with Learning Disabilities (37). No participants were judged to be showing signs of dementia.

Venipunctures were performed for the collection of whole blood, and plasma was isolated from lavender-top EDTA tubes. Complete blood counts were performed on most participants (n = 14 DS and n = 15 controls) via microscopy by trained technicians blinded to sample group.

APOE4 genotyping was performed from blood samples using the 7500 Real-Time PCR System and TaqMan SNP Genotyping Assays (rs429358, rs7412) (Thermo Fisher Scientific), as previously described (38).

Plasma sTREM2 levels were measured using a Luminex 200 3.1 xPONENT System (EMD Millipore, Chicago, IL) and a custom detection method designed to capture the soluble portion of TREM2 protein, as previously described (27). Briefly, a capture Ab bound to MagPlex beads binds sTREM2 (human TREM2 Ab MAB1828 [R&D Systems], monoclonal mouse IgG_2B clone 263602 [His19-Ser174; Immunogen]). A biotinylated Ab with a streptavidin/phycoerythrin conjugate was used for detection (human TREM2 biotinylated Ab BAF1828 [R&D Systems], Ag affinity-purified polyclonal goat IgG [His19-Ser174; Immunogen]). Inflammatory markers were measured with a human cytokine/chemokine panel using Luminex 200 xMap technology and the MILLIPLEX MAP multiplex kits (HCYTMAG60PMX41BK; EMD Millipore) following the manufacturer’s instructions for analyte detection in human plasma. The inflammatory markers in the panel were as follows: epidermal growth factor (EGF), fibroblast growth factor 2 (FGF-2), eotaxin, TGF-α, G-CSF, FMS-like tyrosine kinase 3 ligand (Flt-3L), GM-CSF, fractalkine (also known as CX3CL1), IFN-α2, IFN-γ, growth-regulated oncogene (GRO), IL-10, monocyte chemotactic protein-3 (MCP-3, also known as CCL7), IL-12 40 kDa (IL-12p40), macrophage-derived chemokine (MDC), IL-12 70 kDa (IL-12P70), IL-13, IL-15, soluble CD40-ligand (sCD40L), IL-17A, IL-1 receptor agonist (IL-1RA), IL-1α, IL-9, IL-1β, IL-2, IL-3, IL-4, IL-5, IL-6, IL-7, IL-8, IFN-γ inducible protein 10 kDa (IP-10), MCP-1 (also known as CCL2), macrophage inflammatory protein (MIP) 1α (MIP-1α, also known as CCL3), MIP-1β (also known as CCL4), TNF-α, TNF-β, and vascular endothelial growth factor (VEGF).

DS and control demographics were compared using unpaired t test for age and Fisher exact test for APOE4 status and sex distribution. Plasma sTREM2 and inflammatory markers were measured in plasma on plates that also contained buffer-alone background wells (containing 0 pg/ml of each protein) and standard curve wells containing known concentrations of each protein measured. Concentrations of analytes were determined based on fluorescence of the standard curves for the respective proteins. Concentration values were log₁₀ transformed for comparison. Values below fluorescence levels of the background wells were considered to be physiologically 0 pg/ml and set equal to 0.001 pg/ml to be able to log transform the data. Individual plasma samples were run in duplicate on two different plates, and the overall mean of the four replicates was determined. Replicates with a high coefficient of variation (>30%) were analyzed to identify outliers, which were then removed from the analysis. Complete blood count, biomarker, and inflammatory marker data were compared between groups using unpaired t tests, and false discovery rates (FDR) were determined using the original FDR method of Benjamini and Hochberg, with Q = 1%. Linear regression was used to determine correlations between analytes using SPSS version 22 (IBM, Armonk, NY). Correlograms were made using the “corrplot” function in the corrplot package (39) and arranged according to hierarchical clustering using the Ward method in R version 3.6.1 (R Foundation for Statistical Computing, Vienna, Austria). Heat maps, including hierarchical clustering with the Ward method, were produced using the “heatmap.2” function in the gplots package (40) in R 3.6.1. Data were scaled using the “scale” function in R prior to input into the corrplot and heatmap.2 functions. All other data analysis used GraphPad Prism version 8.1.1 (GraphPad Software, San Diego, CA).

Young adults with DS did not differ significantly from neurotypical controls in terms of age (mean: 29.5 y versus 29.6 y, p = 0.89), distribution of sex (33.3% versus 25.0%, p = 0.70), or presence of the AD risk allele APOE4 (13.3% versus 18.8%, p > 0.99) (Table I).

Plasma sTREM2 was significantly elevated in DS compared with neurotypical controls (p = 0.000966) (Fig. 1A). Markers of inflammation, C-reactive protein (CRP) and erythrocyte sedimentation rate, were compared; CRP was elevated in DS (p = 0.0169), and erythrocyte sedimentation rate trended toward being elevated in DS (p = 0.05098) compared with controls (Fig. 1B, 1C). Participants with DS had significantly higher percentages of basophils (p = 0.000185) and trended toward higher percentages of neutrophils (p = 0.087) compared with controls, whereas percentages of lymphocytes and monocytes did not differ between groups (Fig. 1D). Participants with DS had fewer lymphocytes (p = 0.037) and more basophils (p = 0.001) compared with controls (Fig. 1E) when comparing cell counts.

Given prior observations of elevated peripheral immune factors (15, 16, 18, 41) and our own finding of elevated sTREM2 in DS, we addressed the question of whether other plasma inflammatory markers (cytokines, chemokines, and growth factors) were elevated in our DS cohort using an immune profiling panel. Inflammatory markers were grouped based on known function into the general categories “proinflammatory,” “immunoregulatory/pleiotropic,” and “anti-inflammatory” (42–51). Values below assay background levels were determined to be physiologically 0 pg/ml and set as 0.001 pg/ml for the purpose of log transformation and analysis. Out of the 38 factors tested, 32 were significantly higher in DS compared with age-matched controls (Fig. 2); the exceptions were IL-4, FGF-2, MDC, IL-17A, GRO, and MCP-1. To determine if it was valid to set values below background equal to 0.001, we repeated the analysis after removing all values that had been below background detection levels (Supplemental Fig. 1A). We found that 30 out of 38 cytokines were significantly higher in DS compared with controls; the exceptions were IL-13, G-CSF, IL-6, MDC, IL-17A, GRO, sCD40L, and MCP-1 (Supplemental Fig. 1A, 1B).

Pearson correlations were plotted, and the correlation matrix was clustered based on the Ward method of least variance. Importantly, sTREM2 showed statistically significant correlations only in the group with DS, and in each instance, the correlations were positive. We observed significant positive correlations with sTREM2 and 24 out of 38 measured cytokines in the DS group (MDC, sCD40L, TNF-α, TGF-α, IFN-α2, IL-6, Flt-3L, GM-CSF, IL-1β, IL-12p70, IFN-γ, MIP-1β, IL-17A, VEGF, IL-5, eotaxin, IL-8, IL-3, IL-4, IL-12p40, IL-9, IL-7, Il-10, and IL-15) and 0 out of 38 measured cytokines in the control group (Fig. 3, Pearson correlation coefficients [r] and p values are shown in Supplemental Table I). Additionally, the clustering showed distinctly different patterns in neurotypical controls compared with the DS group (Fig. 3).

To further investigate this relationship, hierarchical clustering of the scaled log₁₀-transformed immune factor concentration values was performed on each group. Lower sTREM2 levels in neurotypical controls (Fig. 1A) clustered closest to GRO, Flt-3L, MDC, and IP-10, whereas higher sTREM2 in the DS group (Fig. 1A) clustered with MDC, sCD40L, and TNF-α (Fig. 4).

In this preliminary report, we found evidence of peripheral inflammation and elevated sTREM2 in a group of young adults with DS without symptoms of dementia. These participants with DS had increased levels of anti-inflammatory, proinflammatory, and immunoregulatory cytokines compared with neurotypical controls, which cannot be explained by known acute or autoimmune illnesses in our cohort. In fact, the DS participants had lower levels of lymphocytes compared with controls. Although the observed basophilia has been reported in DS (52), significantly decreased lymphocyte count and elevated (or trending toward elevated) neutrophils have been reported in AD (53, 54).

Plasma sTREM2 was significantly elevated in DS; interestingly, sTREM2 is elevated in cerebrospinal fluid in the mild cognitive impairment stage of AD and in early-onset forms of AD but not in peripheral biofluids, such as plasma (24, 25, 27, 28, 55). The elevation of sTREM2 in young DS predementia in plasma (Fig. 1A) suggests that peripheral sTREM2 may increase very early in individuals with elevated Aβ. Our previous work showed a relationship between plasma sTREM2 and CRP in AD-related mild cognitive impairment (predementia) (27). This was not observed in this DS predementia cohort. This discrepancy may be related to differing stages of AD-related progression in DS predementia compared with AD-related mild cognitive impairment. An important next study would be to compare peripheral sTREM2 in adults with DS predementia to adults with DS and dementia. These future analyses would help elucidate the role of the innate immunity in the variable age-at-onset of dementia in DS. Additionally, it would be helpful to include other neurotypical control groups, such as APOE ε4 noncarriers at low risk for AD or individuals with systemic inflammatory diseases that are not associated with dementia.

We observed elevated cytokines in the group with DS compared with the neurotypical group. Our findings were similar to another study that found elevated TNF-α, IL-6, and IL-10 in adults with DS predementia (15). Interestingly, this previous report predicted AD development when these inflammatory markers were combined with measures of Aβ (15). In further support of our findings, another report describes increased IL-6, VEGF-A, MCP-1, IL-22, and TNF-α in adults aged 20–65 with DS (56). In contrast, a previous study of adults (mean age 30 y in DS and controls) found elevated serum MIP-1α but not IFN-γ, TNF-α, MIP-1β, RANTES, or IL-6 (57). The similarities across these studies and our own preliminary report support the notion that, in general, the immune response is altered in DS, which may contribute to the development of AD.

Our findings demonstrated that sTREM2 differed in its clustering and correlation patterns between neurotypical and DS groups. Hierarchical clustering linked sTREM2 to different inflammatory markers within the control and DS groups. Because the controls had lower levels of sTREM2, a logical conclusion is that they had more functional, membrane-bound TREM2, an important immune factor for normal innate immunity function (19, 20). This remains to be determined but may have important implications for the cluster analysis results observed. The clustering of sTREM2 with Flt-3L and GRO in neurotypical controls (Fig. 4A) is novel (to our knowledge) information and interesting because Flt-3L is important for proliferation of hematopoietic stem cells. Knockout mice models have shown that it is crucial for the development of hematopoietic progenitor cells, B cells, and dendritic cells (58, 59). Flt-3L was elevated in our DS predementia cohort, suggesting that normally the role of TREM2 cleavage and consequent production of sTREM2 may be related to Flt-3L activity. Although GRO grouped with sTREM2 in controls, it was not significantly elevated in our DS cohort, suggesting a weaker role in DS than Flt-3L. GRO is expressed in monocytes and neutrophils and has proinflammatory and mitogenic functions (60, 61) and may have an important TREM2-related role in normal innate immunity function. TREM2 is similarly involved in cell proliferation, specifically of microglia and macrophages through an interaction with the adapter protein DNAX activating protein of 12 kDa (DAP12) (62).

In contrast, elevated sTREM2 in the DS group clustered with TNF-α, sCD40L, and MDC (Fig. 4B). Whereas MDC had a similar concentration in both the DS and control groups, TNF-α and sCD40L were significantly elevated in DS. TNF-α is an acute-phase cytokine secreted by cells including activated macrophages and brain microglial, which also express TREM2 (58, 63, 64). TNF-α has been implicated in AD pathology numerous times and is reportedly associated with AD progression (65, 66). sCD40L (CD154) is an inflammatory cytokine secreted by activated platelets. It has been shown to be elevated in early AD, and there is evidence that it contributes to disease progression (67–69). MDC (or CCL22) is expressed by activated T cells, NK cells, macrophages, and monocytes and has chemoattractant and inflammatory properties (70). Few studies to date have looked at MDC in the context of AD, but one study found that levels of MDC in cerebrospinal fluid decreased after 1 y of resveratrol treatment in AD compared with the placebo group (71), which may implicate MDC in neuroinflammatory pathways. Together, it was clear that people with DS had an altered relationship between sTREM2 and inflammatory markers, which could be contributing to the accelerated onset of AD in this population.

This is a preliminary report that is limited by the small sample size and potential for false-negative results. DS biomarker studies, including our study, are limited by sample size and should be considered with caution until replicated in larger populations (10, 15, 72, 73). Covariates such as age and APOE4 status did not differ between our two groups but are important to control for in larger future studies. Another limitation of this study is that karyotypes were not available for the DS participants. Although unlikely, given the unique clinical presentation of these two types of patients, it is possible that some of the DS participants had mosaic DS or chromosome 21 translocations, rather than full trisomy 21. This could lead to heterogeneity of the subjects. Additionally, we were not able to collect cerebrospinal fluid from these subjects. Cerebrospinal fluid has been studied more in depth in AD studies compared with plasma and could lend additional evidence of the contribution of sTREM2 and the observed immune state in DS. Furthermore, inclusion of DS with dementia was beyond the limits of this preliminary report. However, future studies of progressive changes in inflammatory markers in not only young adults with DS predementia but also DS of multiple ages, including children with DS and DS with dementia, will greatly enhance our understanding of the role of inflammation in progressive neurodegeneration.

The results of this preliminary report strongly suggest a relationship between plasma sTREM2 and inflammatory markers in DS predementia. We observed significantly elevated inflammatory markers in DS, in agreement with previous reports (16, 18, 41, 74). Notably, we observed a strong positive correlation between many of the tested immune factors and sTREM2 in the group with DS that was not observed in controls. Given that our cohort of young adults with DS were all predementia, these observed correlations with sTREM2 may be early predictors of dementia onset. To our knowledge, this is the first report of a correlation between sTREM2 and multiple inflammatory markers in DS. This finding is supported by previously described dysregulation of the immune response in DS (16, 18, 41, 74) and suggests that TREM2 plays a role in the peripheral immune response in DS predementia.

The authors have no financial conflicts of interest.