Distinctive blood CD56bright NK cell subset profile and increased NKG2D expression in CD56bright NK cells in Parkinson’s disease

Distinctive blood CD56bright NK cell subset profile and increased NKG2D expression in CD56bright NK cells in Parkinson’s disease | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Distinctive blood CD56 bright NK cell subset profile and increased NKG2D expression in CD56 bright NK cells in Parkinson’s disease Jae-Kyung Lee, Stephen Weber, Kelly Menees, Julian Agin-Liebes, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1883506/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 15 Feb, 2024 Read the published version in npj Parkinson's Disease → Version 1 posted 12 You are reading this latest preprint version Abstract Mounting data suggest an important role of the immune system in Parkinson’s disease (PD). Previous evidence of increased natural killer (NK) cell populations in PD suggests a potential role of NK cells in the pathogenesis of the disease. Previous studies have analyzed NK populations using aggregation by a variable expression of CD56 and CD16. It remains unknown what differences may exist between NK cell subpopulations when stratified using more nuanced classification. Here we profile NK cell subpopulations and elucidate the expressions of activating NKG2D receptor, inhibitory NKG2A receptor, and homing CX3CR1 receptor on NK cell subpopulations in PD and healthy controls (HC). The cryopreserved PBMC samples were analyzed using a 10-color flow cytometry panel to assess NK cell subpopulations on 36 individuals with sporadic PD and 35 HC participants. Among PD cases, we observed that NKG2D frequency and expression level was higher in CD56 bright NK populations in patients with more severe motor symptoms as measured by the UPDRS III. Additionally, NKG2D expression intensity in CD56 bright NK populations was associated with disease duration. NK subpopulations revealed a significant difference in CD56 bright CD16 +/− NK cell subpopulations, with all PD groups showing significantly greater expression of NKG2D on CD56 bright CD16 bright NK cells compared to HC. Overall, we identified changes in NK profiles in PD that change with disease duration and motor symptom severity. Future studies should assess whether these changes in NK populations account for disease progression. Natural killer (NK) cells NKG2D NKG2A CX3CR1 Parkinson’s Disease UPDRS Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Recent evidence has implicated the role of neuroinflammation (thoroughly reviewed in 1 ) in PD pathogenesis. Moreover, changes in peripheral immune cell distributions have been documented in PD patients 2 , 3 . Of particular interest are natural killer (NK) cells, an innate immune system population, traditionally associated with the destruction of malignant cells following signaling through activating and inhibitory receptors resulting in cytotoxicity mediated via perforin and granzyme 4 , 5 . A recent study utilizing the preformed fibril (PFF) α-syn mouse model of PD demonstrated infiltration of NK cell in the central nervous system (CNS) and altered frequency and numbers in the periphery 5 months post-injection 6 . Furthermore, NK cells were shown to internalize and degrade α-syn aggregates and systemic depletion of NK cells in a preclinical mouse model of PD exacerbated synuclein pathology and motor symptoms, further implicating NK cells as a relevant cell type in PD pathogenesis 7 . Recent work in a murine model showed that NK cell numbers declined and showed functional deficits in α-syn clearance with age, highlighting the necessity for further characterization of NK cells in PD patients to elucidate profile differences 8 . Interestingly, studies have found increased total NK cell numbers in PD patients compared to non-PD controls 2,3,9−12 highlighting a key opportunity to explore NK cells as a biomarker for PD. Human NK cells have historically been broadly classified by their expression of cell surface markers, cluster of differentiation (CD) 56 (neural cell adhesion molecule) and CD16 (Fcγ Receptor III) and being CD3 negative. Distinct NK cell subpopulations in humans have been identified based on variable expression of CD56 and CD16: CD56 bright CD16 − , CD56 bright CD16 dim , CD56 dim CD16 − , CD56 dim CD16 bright , and CD56 − CD16 bright 13 . The majority, upwards of 90%, of blood circulating NK cells are CD56 dim CD16 +/− with the remainder being predominantly CD56 bright CD16 dim/− and the smallest minority being CD56 − CD16 bright 13 . It remains actively debated the developmental progression for NK cell expression of CD56, but many consider the CD56 bright CD16 dim/− population as the precursor to CD56 dim CD16 bright populations. CD56 bright CD16 dim/− are abundant cytokine producers while CD56 dim CD16 bright are the predominant cytotoxic population 5 , 13 . In addition to expression of CD56 and CD16, differential expressions of activating and inhibitory receptors are shown to mediate NK cell activity 5 , 14 , 15 . The cumulative sum of activating and inhibitory signaling directly regulates NK cell effector functions, such as cytotoxicity. Natural killer group 2D (NKG2D) recepter is an activating receptor constitutively expressed on NK cells 16 . Alterations in NKG2D have previously been reported in PD patients (summarized in 17 )The frequency of NKG2D + NK cells have been reported to be unchanged 10 and increased in PD patient samples compared to healthy controls 11 . Natural killer group 2A (NKG2A) receptor is an inhibitory receptor expressed by NK cells that recognizes histocompatibility antigen, alpha chain E (HLA-E), also known as major histocompatibility complex (MHC) class I antigen E. NKG2A + NK cells have previously been reported to be decreased in PD patients compared to controls 10 . The interaction between chemokine C-X3-C motif receptor 1 (CX3CR1) and its ligand CX3CL1 (also known as fractalkine) mediates immune cell chemotaxis 18 , 19 . Expression of CX3CR1 has been shown to be essential for NK cell homing to the CNS and ameliorating disease in an experimental autoimmune encephalomyelitis (EAE) model of multiple sclerosis 20 . As NK cells have been demonstrated to be present in brains of patients with synucleinopathies and in mouse models of PD 6 , 7 , assessing CX3CR1 expression in PD patients warrants further investigation. Discovery of distinct immune cell receptor profiles representing early diagnostic biomarkers provides an opportunity for earlier intervention and treatment. To date, a comprehensive analysis of NK subpopulations and their variable expression of activating and inhibitory receptors in PD has not been carried out. Here we analyzed the frequency and expression intensity of NK receptors, NKG2D, NKG2A and CX3CR1, by NK subsets and parsed NK subsets into 6 NK subpopulations to resolve additional NK cell profile differences. Peripheral blood samples of 71 donors (36 PD, 35 HC) were analyzed by conventional flow cytometry. Using mean fluorescence intensity (MFI), we evaluated the variable expression of markers of interest to quantify distinct profiles representing differences between HC and PD samples. We used the total score of Unified Parkinson’s Disease Rating Scale (UPDRS) part III and PD duration to stratify the differences across NK cell subpopulations. Results NK Cell Frequency is Comparable between PD and Healthy Control Historically, NK cell populations have been aggregated along variable expressions of CD56: CD56 bright , CD56 dim and, the rarely included, CD56 − . Here we included NK subset population outcomes and expanded analysis utilizing six subpopulations based on CD56 and CD16 expression defined previously 13 . Cryopreserved peripheral blood mononuclear cells (PBMCs) from 71 donors, (36 PD, 35 HC; Table 1 ) were thawed and processed for flow cytometry analysis. Using our 10-parameter panel we investigated six NK cell subpopulations: (1) CD56 bright CD16 − , (2) CD56 bright CD16 dim , (3) CD56 dim CD16 − , (4) CD56 dim CD16 dim , (5) CD56 dim CD16 bright , and (6) CD56 − CD16 + (Fig. 1 A). Population gates were established using quantitatively determined antibody titrations, gates set using single color and fluorescence minus one (FMO) control, and compensation to reduce fluorescent spill-over. Only live single cell populations were analyzed, to prevent non-specific binding artifacts or misrepresentation due to doublets. The frequencies of cells expressing CD45 + (hematopoietic), CD3 + (T cells), CD3 − CD14 + CD19 + (B cells/monocytes), and CD3 − CD14 − CD19 − (NK cells) were not significantly different between PD or HC (Fig. 1 B). In alignment with previous literature assessing NK cell subsets in PBMCs, we quantified CD56 bright CD16 +/− , CD56 dim CD16 +/− , and CD56 − CD16 + NK cell frequencies and found no significant differences between PD or HC (Fig. 1 C). Frequency of NKG2D + CD56 bright NK cells increased with higher UPDRS III scores To date, differences that may exist in the activating and inhibitory receptor profiles in NK cell populations as PD motor severity increases have yet to be defined. We began by stratifying PD samples into three groups based on the severity of their motor symptoms using the UPDRS-III as a marker of severity. A score of < 20 corresponds with mild motor symptoms, 20–32 with moderate motor symptoms, and 32 + with severe motor symptoms and examined differences in the frequency of NK cells by subpopulations, and their expression of NKG2D, NKG2A and CX3CR1 were assessed. While differences in aggregate populations in PD have been identified previously 2,3,9−12 , we sought to further characterize the spectrum of changes that may exist across NK cell populations in relation to UPDRS III motor scores. Through analysis of CD56 bright CD16 +/− NK cell subpopulations we found a significantly lower frequency of CD56 bright CD16 + than CD56 bright CD16 − NK cells in HC (p < 0.0001) compared to patients with UPDRS 20 lacked this difference (Fig. 2 A). Within the CD56 dim CD16 +/− NK cell subpopulations, HC samples showed a significantly lower frequency of CD56 dim CD16 − NK cells compared to CD56 dim CD16 dim NK cells (p < 0.0001) and CD56 dim CD16 bright NK cells (p < 0.0001). In the UPDRS 32 + group a significantly lower frequency of CD56 dim CD16 − NK cells compared to CD56 dim CD16 dim (p = 0.0052) and CD56 dim CD16 bright NK (p < 0.0001) was observed (Fig. 2 B). Additionally, the frequency of CD56 dim CD16 bright NK cells was significantly less in the UPDRS < 20 group than in the UPDRS 20–32 group (p = 0.0323). The UPDRS 20–32 group showed a significant increase in frequency of the CD56 dim CD16 bright subpopulation compared to the CD56 dim CD16 − (p < 0.0001) and CD56 dim CD16 dim (p = 0.0009) NK cells (Fig. 2 B). No significant differences were observed in the CD56 − CD16 + NK cell population across UPDRS III score groups (Fig. 2 C). The overactivation of NK populations via activating receptors represents a potential explanation for the sustained and progressive neuroinflammation in PD, herein we assessed alterations in the frequency of NKG2D, an activating receptor, on NK cell populations in relation to UPDRS III scores. Assessment of CD56 bright CD16 +/− NK cell subset showed the frequency of activating receptor NKG2D was significantly increased in UPDRS 20–32 (p = 0.0153) and UPDRS 32+ (p = 0.0489) compared to samples from participants with UPDRS scores < 20 (Fig. 3 A). No significant differences in frequencies of NKG2D + cells were observed in the CD56 dim CD16 +/− or CD56 − CD16 + NK cell subsets (Fig. 3 B-C). Further stratification of the CD56 bright CD16 +/− NK cells into CD56 bright CD16 + and CD56 bright CD16 − NK cell subpopulations revealed a significant decrease in NKG2D in the CD56 bright CD16 − versus the CD56 bright CD16 + NK cells in samples with UPDRS scores < 20 (p = 0.0026) (Fig. 3 D). Across all HC and PD groups, a significant increase in NKG2D frequency was observed when comparing CD56 dim CD16 − and CD56 dim CD16 dim NK cells to CD56 dim CD16 bright NK cells, with the highest frequency of NKG2D observed in the CD56 dim CD16 bright NK cells (p < 0.0001) (Fig. 3 E). Interestingly, in HC there was a significant increase in NKG2D frequency in CD56 dim CD16 dim NK cells compared to the CD56 dim CD16 − NK cells (p = 0.0015) (Fig. 3 E). This difference was not observed in the remaining PD groups. Conversely to the potential action of NKG2D, changes to inhibitory receptor NKG2A represent an alternative mechanism of change for NK cell function that may slow PD progression. Analysis of the frequency of NKG2A + cells across UPDRS scores showed no significant differences between aggregate NK cell subsets (Fig. 3 F-H). Additionally, investigation of CD56 bright CD16 +/− NK cell subpopulations showed no significant differences in frequency of NKG2A across UPDRS scores (Fig. 3 I). However, a significant decrease in NKG2A frequency was observed in CD56 dim CD16 bright NK cells compared to CD56 dim CD16 − NK cells in both HC and UPDRS score 20–32 (Fig. 3 J). Alterations to activation and inhibitory receptor profiles on NK cells may not represent the entirety of contributing factors in PD severity progression. Aberrant homing of NK cells to the brain may underlie increased risk of cytotoxicity to dopamine (DA) neurons. To understand this, we investigated NK homing receptor CX3CR1, which has been found to guide NK cells to the brain. Our results showed no significant differences in CX3CR1 frequency across NK subsets (Fig. 3 K-M) or within CD56 bright CD16 +/− NK cell subpopulations (Fig. 3 N). In the CD56 dim NK cell subpopulations, HC had a significantly greater frequency of CX3CR1 on CD56 dim CD16 dim (p = 0.0002) and CD56 dim CD16 bright (p < 0.0001) NK cells than CD56 dim CD16 − NK cells (Fig. 3 O). PD groups UPDRS < 20 and 20–32 also had a significant increase in the frequency of CD56 dim CD16 bright NK cells compared to CD56 dim CD16 − NK cells (p = 0.0196 and p = 0.0262, respectively) observed in HC samples (Fig. 3 O). Expression of NKG2D is increased in CD56 bright CD16 + NK cells in PD groups with UPDRS score < 32 The binary presence or absence, or frequency, of a receptor on NK cells may not provide the depth of detail necessary to understand changes at the receptor level; therefore, to aptly reflect the potential bias towards activation or inhibition, we assessed the mean fluorescence intensity (MFI) to evaluate the variability in expression intensity of receptors in NK cell profiles. We found a significant increase in NKG2D expression on CD56 bright CD16 +/− NK cells with a UPDRS score 20–32 compared to UPDRS score < 20 (p = 0.0287) (Fig. 4 A). No significant differences were observed in the MFI of NKG2D or NKG2A for the remainder of NK subsets (Fig. 4 B-C). We observed a significant increase in the expression of NKG2D in the CD56 bright CD16 + NK cell subpopulation compared to the CD56 bright CD16 − NK cells in UPDRS < 20 (p = 0.023) and 20–32 (p = 0.041) groups (Fig. 4 D). The CD56 dim CD16 bright NK cells displayed significantly increased expression of NKG2D compared to the CD56 dim CD16 − and CD56 dim CD16 dim NK cells, and this was conserved across HC and PD groups (p < 0.0001) (Fig. 4 E). No significant differences were observed in expression of NKG2A for NK subsets or NK subpopulations (Fig. 4 F-J). Lastly, assessment of CX3CR1 expression showed no significant changes across NK cell subsets or subpopulations (Fig. 4 K-O). Increased frequency of NKG2A in CD56 bright NK cells observed with longer disease duration. To assess changes that may correlate with different stages of PD we subdivided PD patients into three groups according to the disease duration at sampling: <5yrs (early), 5-10yrs (intermediate), 10 + yrs (late) and investigated the frequency of NKG2D, NKG2A and CX3CR1 across NK cell populations Total NK cell frequency evaluation showed a significantly reduced CD56 bright CD16 + NK cell subpopulation compared to CD56 + CD16 − NK cells in HC (p < 0.0001) but not PD (Fig. 5 A). In CD56 dim NK cells, the CD56 dim CD16 bright NK cells showed a significantly greater frequency compared to CD56 dim CD16 − NK cells in HC (p < 0.0001), PD < 5yrs (p < 0.0001), 5-10yrs (p < 0.0001), and 10 + yrs (p = 0.031) (Fig. 5 B). Interestingly, a significantly greater frequency of CD56 dim CD16 dim NK cells compared to CD56 dim CD16 − NK cells was observed in HC (p < 0.0001) and PD durations < 5yrs (p = 0.017) and 5-10yrs (p = 0.0494); however, this was not present in samples with a PD duration 10 + yrs (Fig. 5 B). Additionally, in samples with PD duration < 5yrs, a significantly greater frequency of CD56 dim CD16 bright NK cells was observed compared to CD56 dim CD16 dim NK cells (p = 0.001) which was not present in HC or other PD groups (Fig. 5 B). No differences in the CD56 − NK cell population were observed across HC and PD groups (Fig. 5 C). We assessed differences in NK population frequencies for both subsets and subpopulations for activating receptor NKG2D, inhibitory receptor NKG2A, and homing receptor CX3CR1. We found no significant differences in NKG2D (Fig. 6 A-C) expression frequency in NK subsets when clustered by disease duration. Conversely, we observed a significantly reduced frequency of NKG2D expression in the CD56 bright CD16 − NK cells compared to the CD56 bright CD16 + NK cells at < 5yrs PD duration (p = 0.002) that was not present in HC or other PD duration groups (Fig. 6 D). Strikingly, in HC a significantly increased NKG2D frequency was observed in the CD56 dim CD16 dim NK cells compared to the CD56 dim CD16 − NK cells (p = 0.001) that was not observed in PD groups; however, all groups showed a significantly higher NGK2D frequency in the CD56 dim CD16 dim and CD56 dim CD16 bright NK cells compared to the CD56 dim CD16 − NK cells (p < 0.0001) (Fig. 6 E). We found a significantly greater frequency of NKG2A in the CD56 bright CD16 +/− subset in the group with 10 + yrs PD duration compared to the group with < 5yrs of PD duration (p = 0.025) (Fig. 6 F) but no significant differences in CD56 dim CD16 +/− or CD56 − CD16 +/− NK cell subsets (Fig. 6 G-H). Analysis of NK subpopulations showed no significant changes in CD56 bright subpopulations (Fig. 6 I); however, a significant reduction in NKG2A frequency of CD56 dim CD16 bright NK cells compared to CD56 dim CD16 − NK cells were observed in HC (p = 0.0005) and 10 + yrs PD duration (p = 0.023) (Fig. 6 J). No significant differences in expression frequency of CX3CR1 were observed in NK subsets (Fig. 6 K-M) or in CD56 bright CD16 +/− NK cell subpopulations (Fig. 6 N). Conversely, HC (p < 0.0001), <5yrs (p < 0.0001), and 5-10yrs (p < 0.0002) PD duration groups showed a significantly greater CX3CR1 frequency in the CD56 dim CD16 bright NK cells in comparison to the CD56 dim CD16 − NK cells, but this was absent in PD group 10 + yrs (Fig. 6 O). Interestingly, HC (p = 0.002) and the 5-10yrs PD duration group (p = 0.0008) had a significantly lower CX3CR1 frequency in the CD56 dim CD16 − population compared to CD56 dim CD16 dim population but this was not present in PD groups < 5 yrs or 10 + yrs (Fig. 6 O). Furthermore, the CD56 dim CD16 − NK cells from PD group 5-10yrs showed a significantly higher frequency of CX3CR1 than the same population from the PD group 10 + yrs (p = 0.044) (Fig. 6 O). Expression of NKG2D is increased in CD56 bright and CD56 dim NK cells with longer PD disease duration. To address distinctive changes in receptor expression we included analysis of expression measured by MFI to ensure a robust understanding of the receptor profiles within these populations over time in PD. The expression of activating receptor, NKG2D, showed no significant difference in the CD56 bright CD16 +/− NK cell subset (Fig. 7 A) but was found to be significantly greater in the CD56 dim CD16 +/− NK cell subset in PD 5-10yrs versus HC (p = 0.045) (Fig. 7 B). CD56 − NK cell subset showed no significant difference in expression of NKG2D (Fig. 7 C). Importantly, analysis of subpopulations revealed that all PD groups had a significantly greater expression of NKG2D in CD56 bright CD16 + NK cells compared to HC (p < 0.0001) (Fig. 7 D). Additionally, PD < 5yrs (p = 0.0001), PD 5-10yrs (p = 0.002), and PD 10 + yrs (p = 0.033) had a significantly greater expression of NKG2D on CD56 bright CD16 + NK cells compared to CD56 bright CD16 − NK cells (Fig. 7 D). We observed significantly greater expression of NKG2D on CD56 dim CD16 bright NK cells compared to CD56 dim CD16 − NK cells in all groups (p < 0.0001) (Fig. 7 E). Significantly increased expression of NKG2D on CD56 dim CD16 bright NK cells compared to CD56 dim CD16 dim NK cells was observed across HC, PD < 5yrs, 5-10yrs (p < 0.0001) and 10 + yrs (p = 0.0004) (Fig. 7 E). Inhibitory receptor NKG2A was found to have a significantly greater expression in the CD56 bright CD16 +/− NK cell subset at PD 5-10yrs compared to PD < 5yrs (p = 0.045) (Fig. 7 F). No other significant differences in MFI were observed for NKG2A (Fig. 7 G-J). No significant differences in the expression of CX3CR1 were observed (Fig. 7 K-O). Discussion Previously, analysis of NK populations in PD has been done using NK cell subset analysis based on variable expression of CD56 and CD16, with minimal inclusion of CD56 − . Here we show, defining NK cell profiles with granular and functional subpopulations allows for deeper understanding of changes within NK populations in PD. Analysis of expression frequency and MFI within each group to assess receptors NKG2D, NKG2A and CX3CR1, enabled us to outline a profile for the subtle changes within these NK cell populations. While our results show no significant difference in the frequency of NK cells between HC and PD patients using CD56 and CD16 2,12 , this is unsurprising as the statistical significance may be absent due to our reduced population size for both PD and HC. However, our NK cell population frequencies for both PD and HC align with previous findings 2 . Additionally, our results corroborate previous findings on receptor expression profiles within aggregate NK populations, such as the variable expression of NKG2D, NKG2A, and CX3CR1 on CD56 bright , CD56 dim , and CD56 − NK subsets 13 , 15 . Understanding of the relationship between these NK receptors over the course of PD facilitates establishment of disease profiles that can inform the role of NK cells in PD along with enabling development of clinical treatment options. Nuanced NK cell subpopulation profiles are a necessity for parsing key differences that may exist in PD progression, with these defined profiles insights on biomarkers that can be used to classify critical windows for intervention may be uncovered. To accomplish this, we assessed NKG2D and NKG2A in an effort to define the involvement of activating and inhibitory signaling, respectively, that underlie immune context changes that can inform understanding of PD progression and severity. NK populations exhibit distinct functional differences based on the binary presence or absence in conjunction with the expression intensity of a repertoire of receptors, meriting the necessity to define differences that may reflect important profile changes. These differences may represent readily observable biomarker changes in these variable populations over the course of disease that can inform treatment and diagnosis. Our analysis shows significant changes within CD56 bright CD16 +/− and CD56 dim CD16 +/− populations with respect to the frequency of NKG2D and NKG2A, offering valuable insight into the immunomodulatory and cytotoxicity context that NK cells may mediate in PD patients. Most importantly, we show the CD56 bright CD16 +/− NK cell subset and subpopulations have increased NKG2D frequency and expression, suggesting an increased activation potential for the CD56 bright CD16 +/− NK cell subset in PD patients. With the CD56 bright CD16 +/− NK cell subset traditionally attributed with a primary role as immunomodulators via cytokine production and release 13 , the increased activation of this population may correlate with changes in immune activity underlying changes in disease severity. Interestingly, we also found a significant increase in NKG2D expression as PD duration increased compared to HC in CD56 bright CD16 + , suggesting a potential increase in activation potential for this population compared to HC. Taken together these findings highlight that CD56 bright CD16 + NK population overactivation in PD may correlate with increases in pathology. In conjunction with our findings that no significant increases in NKG2A expression were discovered, there may be a disproportionate increase in activation signaling via NKG2D on NK cells in patients with PD, resulting in a pathological change that requires further investigation to define the role this change has in PD patients. Further understanding of the impact that increased activation receptor frequency and expression has in the interplay between NK cells and adjacent immune cell populations may provide clarity on the role NK cells have in altering the immune landscape. Defining this relationship enables development of targeted interventions to alter the immune context underlying PD progression. Materials And Methods Samples PBMC samples were collected in sodium citrate-coated tubes following ficoll gradient separation, suspended in dimethyl sulfoxide (DMSO) cryopreservation buffer, and stored at -80°C by the Roy Alcalay Lab at Columbia University. Samples were delivered on dry ice and upon delivery samples were immediately stored at -80°C until use. Control Samples: female n = 20, male n = 16 (1 null); PD samples: female n = 18 (1 null), male n = 18 (sample demographics are outlined in Table 1). The study protocol for human blood collection and the consent form was reviewed and approved by the Institutional Review Boards of The Columbia University. Participants were provided with informed consent. The coded samples were shared between Columbia University and University of Georgia and the unblinding occurred after all samples were processed and when the data was analyzed. Thawing and Preparation of PBMCs PBMC processing was adapted from Barcelo et al., 2018 21 . Cryopreserved samples were submerged halfway for 60 seconds in a 37°C water bath. Immediately prior to full sample thaw 1 mL of pre-warmed (37°C) complete RPMI (RPMI, 10% FBS, 1% Pen/Strep) was added dropwise, pipetted against the tube wall. Thawed PBMCs were poured into a 15 mL conical tube containing 5 mL of pre-warmed (37°C) complete RMPI. Cryovials were rinsed with 2 mL of pre-warmed (37°C) complete RPMI and then poured into the previously used conical tube with cell mixture. PBMCs were incubated for 5 minutes in a 37°C water bath. PBMCs were then pelleted for 10 minutes at 1500 rpm, at room temperature. Supernatant was discarded and 1 mL of pre-warmed (37°C) complete RPMI with 50 U/mL of DNase (Roche, Cat# 04-716-728-001, 10 units/µL) was added, resuspension was done without pipetting. PBMCs were then incubated for 1 hour at 37°C in a water jacketed incubator (5% CO 2 , 95% humidity) with tube cap loosened. Following incubation PBMCs were pelleted and resuspended for counting in preparation for flow cytometry. Antibodies, Titration and Staining Protocol Antibody Titration All antibodies and Live/Dead stain: CD45-PacBlue (1:200, clone HI30, BioLegend), CD14-PerCP/Cy5.5 (1:100, HCD14, BioLegend), CD19-PerCP/Cy5.5 (1:100, HIB19, BioLegend), CD3-APC/Cy7 (1:50, HIT3a, BioLegend), CD56-APC (1:100, HCD56, BioLegend), CD16-PE/Cy7 (1:100, 3G8, BioLegend), NKG2D-FITC (1:100, 1D11, BioLegend), NKG2A-PE (1:100, 131411, R&D), CX3CR1-BV711 (1:100, 2A9-1, BioLegend), and Zombie Yellow (423103, BioLegend) were individually titrated using Veri-Cells (Cat# 425001, BioLegend) to determine optimal staining concentrations. Staining Prepared PBMCs were transferred to a 96-well plate, pelleted (1,500rpm for 5 minutes at room temp) and washed with PBS. PBMCs were incubated with Zombie Yellow (1:500) for 20 minutes, at room temperature, in the dark. PBMCs were washed with FACS Buffer (0.1% BSA, 1 mM EDTA, 0.01% Sodium Azide, and PBS) and pelleted. Samples were then resuspended in FACS Buffer with Human TruStain FcX (1:20, Cat# 422302, BioLegend) for 10 minutes at room temperature. Samples were then pelleted and resuspended in antibody master mix at a ratio of 1x10 6 cells/100µL master mix. Cells were incubated for 20 minutes at room temperature in the dark. Cells pelleted and washed twice with PBS. Prior to analysis samples were pelleted and resuspended in 2% paraformaldehyde. Samples were analyzed immediately after preparation. Single-color controls were prepared for each run using UltraComp eBeads (Cat# 01-2222-42, Thermo Fisher Scientific). Flow Cytometry: Acquisition and Experimentation Standardization Samples were analyzed using a NovoCyte Quanteon Flow Cytometer (Agilent Technologies). The system used has 4 excitation lasers: 405 nm, 488 nm, 561 nm and 640 nm. Prior to sample analysis, instrumentation performance was evaluated by the quality control (QC) procedure, experiments were only run if performance was optimal. To establish study standardization longitudinally, antibody titration was performed, and optimal antibody concentrations were determined. Using optimal antibody concentrations, instrument gain settings were established for each parameter by evaluation of single-positive signals and confirmation that all positive events were below the maximum dynamic range of the instrument (7.2 log). Using established gains for all parameters, compensation was calculated, fluorescence minus one (FMO) controls, and single color controls were collected, to ensure downstream analysis accuracy of determined positive event populations. A minimum of 100,000 events were collected per sample to ensure robust breadth of population distributions. Statistical Analysis and Quantitation Analysis of flow cytometry data was carried out using FlowJo 10.8 (BD Biosciences). Statistical analysis was performed using Graphpad Prism (Graphpad Software, v9.3.1). A P-value of less than 0.05 was considered statistically significant. Data Availability The datasets generated during and/or analyzed during the current study are available from the corresponding author. Declarations Acknowledgements This study was supported by MJFF Research Grant ID MJFF-019068 and NIH/NINDS R01NS119610-01. Conflict of Interest The authors have no conflict of interest to report. Author Contributions S.W. performed the experiments on PBMCs, the data analysis and wrote the manuscript. K.B.M. performed the data analysis of PMBCs and wrote the manuscript. R.N.A. selected the patient cohort for the PBMC and provided data interpretation. J.A.L, and C.C.L provided data interpretation. J.K.L conceived the experimental plan, supervised the work and wrote the manuscript. All the authors contributed to the manuscript preparation. References Pajares, M., I. Rojo, A., Manda, G., Boscá, L. & Cuadrado, A. Inflammation in Parkinson’s Disease: Mechanisms and Therapeutic Implications. 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J Neuroinflammation 16 , 250, doi: 10.1186/s12974-019-1636-8 (2019). Earls, R. H. et al. NK cells clear alpha-synuclein and the depletion of NK cells exacerbates synuclein pathology in a mouse model of alpha-synucleinopathy. Proc Natl Acad Sci U S A 117 , 1762–1771, doi: 10.1073/pnas.1909110117 (2020). Menees, K. B. et al. Sex- and age-dependent alterations of splenic immune cell profile and NK cell phenotypes and function in C57BL/6J mice. Immun Ageing 18 , 3, doi: 10.1186/s12979-021-00214-3 (2021). Huang, Y. et al. Significant Difference of Immune Cell Fractions and Their Correlations With Differential Expression Genes in Parkinson’s Disease. Frontiers in Aging Neuroscience 13 , doi: 10.3389/fnagi.2021.686066 (2021). Mihara, T. et al. Natural killer cells of Parkinson's disease patients are set up for activation: a possible role for innate immunity in the pathogenesis of this disease. Parkinsonism Relat Disord 14 , 46–51, doi: 10.1016/j.parkreldis.2007.05.013 (2008). Niwa, F., Kuriyama, N., Nakagawa, M. & Imanishi, J. Effects of peripheral lymphocyte subpopulations and the clinical correlation with Parkinson's disease. Geriatr Gerontol Int 12 , 102–107, doi: 10.1111/j.1447-0594.2011.00740.x (2012). Tian, J. et al. Specific immune status in Parkinson’s disease at different ages of onset. npj Parkinson's Disease 8 , 5, doi: 10.1038/s41531-021-00271-x (2022). Poli, A. et al. CD56bright natural killer (NK) cells: an important NK cell subset. Immunology 126 , 458–465, doi: 10.1111/j.1365-2567.2008.03027.x (2009). Amand, M. et al. Human CD56dimCD16dim Cells As an Individualized Natural Killer Cell Subset. Frontiers in Immunology 8 , doi: 10.3389/fimmu.2017.00699 (2017). Michel, T. et al. Human CD56 bright NK Cells: An Update. The Journal of Immunology 196 , 2923–2931, doi: 10.4049/jimmunol.1502570 (2016). Molfetta, R., Quatrini, L., Santoni, A. & Paolini, R. Regulation of NKG2D-Dependent NK Cell Functions: The Yin and the Yang of Receptor Endocytosis. Int J Mol Sci 18 , doi: 10.3390/ijms18081677 (2017). Menees, K. B. & Lee, J. K. New Insights and Implications of Natural Killer Cells in Parkinson's Disease. J Parkinsons Dis, doi: 10.3233/jpd-223212 (2022). Imai, T. et al. Identification and molecular characterization of fractalkine receptor CX3CR1, which mediates both leukocyte migration and adhesion. Cell 91 , 521–530 (1997). Sciume, G. et al. CX3CR1 expression defines 2 KLRG1 + mouse NK-cell subsets with distinct functional properties and positioning in the bone marrow. Blood, The Journal of the American Society of Hematology 117 , 4467–4475 (2011). Huang, D. et al. The neuronal chemokine CX3CL1/fractalkine selectively recruits NK cells that modify experimental autoimmune encephalomyelitis within the central nervous system. Faseb j 20 , 896–905, doi: 10.1096/fj.05-5465com (2006). Barcelo, H., Faul, J., Crimmins, E. & Thyagarajan, B. A Practical Cryopreservation and Staining Protocol for Immunophenotyping in Population Studies. Current Protocols in Cytometry 84 , e35, doi: https://doi.org/10.1002/cpcy.35 (2018). Additional Declarations (Not answered) Cite Share Download PDF Status: Published Journal Publication published 15 Feb, 2024 Read the published version in npj Parkinson's Disease → Version 1 posted Editorial decision: revise 26 Sep, 2022 Review # 2 received at journal 16 Sep, 2022 Review # 3 received at journal 01 Sep, 2022 Reviewer # 3 agreed at journal 24 Aug, 2022 Reviewer # 2 agreed at journal 24 Aug, 2022 Review # 1 received at journal 21 Aug, 2022 Reviewer # 1 agreed at journal 08 Aug, 2022 Reviewers invited by journal 07 Aug, 2022 Submission checks completed at journal 26 Jul, 2022 Unknown event 22 Jul, 2022 Editor assigned by journal 21 Jul, 2022 First submitted to journal 21 Jul, 2022 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1883506","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":127096097,"identity":"7a9cc56f-6d50-43c9-bb20-272f536659e5","order_by":0,"name":"Jae-Kyung Lee","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAu0lEQVRIiWNgGAWjYBACxgYGxgMMDDYQHg+RWhiAWtJI0AICQC2HSdDC3H464cCHivOJ890PMD5420aMw3pyNxycceZ24sYzCcyGc4nS0pC74TBvG1BLQwKbNC9RWvrfbjj899+5xI39D9h/E6dlBtAWxoYDifMlEtiYidTydsPBnmPJxhskHjZLzjlHhBbD/tyND37U2MnO708++OFNGTFaGqAMgwOMDXjUIQF5OINIDaNgFIyCUTACAQABUUDEXcobZwAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0003-0104-8623","institution":"University of Georgia","correspondingAuthor":true,"prefix":"","firstName":"Jae-Kyung","middleName":"","lastName":"Lee","suffix":""},{"id":127096098,"identity":"5344fbbe-5dcd-49e0-aae2-7d9f1f7d9aaa","order_by":1,"name":"Stephen Weber","email":"","orcid":"","institution":"University of Georgia","correspondingAuthor":false,"prefix":"","firstName":"Stephen","middleName":"","lastName":"Weber","suffix":""},{"id":127096099,"identity":"47c6d4ea-07f2-49a4-a976-b6f48d94346f","order_by":2,"name":"Kelly Menees","email":"","orcid":"https://orcid.org/0000-0003-4282-8546","institution":"University of Georgia","correspondingAuthor":false,"prefix":"","firstName":"Kelly","middleName":"","lastName":"Menees","suffix":""},{"id":127096100,"identity":"3ef37239-7279-4411-9d19-3fb862c2e94f","order_by":3,"name":"Julian Agin-Liebes","email":"","orcid":"","institution":"Columbia University","correspondingAuthor":false,"prefix":"","firstName":"Julian","middleName":"","lastName":"Agin-Liebes","suffix":""},{"id":127096101,"identity":"a182da88-f326-43d0-aede-984e9ab3a3c7","order_by":4,"name":"Chih-Chun Lin","email":"","orcid":"","institution":"Columbia University","correspondingAuthor":false,"prefix":"","firstName":"Chih-Chun","middleName":"","lastName":"Lin","suffix":""},{"id":127096102,"identity":"f4b82327-c1e1-4590-b7a9-b8306db17c1f","order_by":5,"name":"Roy Alcalay","email":"","orcid":"","institution":"Columbia University","correspondingAuthor":false,"prefix":"","firstName":"Roy","middleName":"","lastName":"Alcalay","suffix":""}],"badges":[],"createdAt":"2022-07-22 00:40:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1883506/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1883506/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41531-024-00652-y","type":"published","date":"2024-02-15T05:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":25000742,"identity":"ab15b905-9387-46cf-861a-0b590dbbcb10","added_by":"auto","created_at":"2022-08-09 17:59:15","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":616465,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLeukocyte frequency is unchanged in PD patients compared to healthy controls. \u003c/strong\u003e(A) NK cell gating strategy. Cells were first gated on forward scatter (FSC) and the live/dead marker Zombie Yellow to only include live cells. The live cell population was then gated on a FSC and side scatter (SSC). From the CD45+ population, NK cells were then gated from the CD14/19 negative CD3 negative population. NK cell subsets were gated based on CD56 and CD16 expression. (B) Frequency of total leukocytes, T cells, B cells/monocytes, and NK cells in PD patients and healthy controls. (C) Frequency of CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+/-\u003c/sup\u003e, CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e+/-\u003c/sup\u003e, and CD56\u003csup\u003e-\u003c/sup\u003eCD16\u003csup\u003e+\u003c/sup\u003e NK cells in PD patients and healthy controls. Data were analyzed by one-way ANOVA. Data represent mean ± SEM.\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-1883506/v1/3fb9d4f344bbc9c0277246ba.png"},{"id":25001570,"identity":"f87845f9-ad96-4d46-99f0-a0c846d230bf","added_by":"auto","created_at":"2022-08-09 18:04:15","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":27353,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFrequencies of CD56\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003edim\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e NK cell subpopulations are altered with UPDRS scores.\u003c/strong\u003e Plots show frequency of total NK cells of CD56\u003csup\u003ebright\u003c/sup\u003e subpopulations (A), CD56\u003csup\u003edim\u003c/sup\u003e subpopulations (B), and CD56\u003csup\u003e-\u003c/sup\u003eCD16\u003csup\u003e+\u003c/sup\u003e (C) from HC and PD samples stratified by UPDRS score (\u0026lt;20, 20-32, 32+). Data were analyzed by two-way ANOVA followed by Tukey’s post hoc analysis. Data represent mean ± SEM. *\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, ***\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001, ****\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.0001.\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-1883506/v1/636f2f48d6da85bf285fb508.png"},{"id":25000741,"identity":"e3f3f862-c31f-493a-b030-3846e0c2c0ed","added_by":"auto","created_at":"2022-08-09 17:59:14","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":91160,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFrequency of NKG2D+ CD56\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ebright\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e NK cells increased with greater UPDRS scores. \u003c/strong\u003e(A, B, C) Plots show frequency of NKG2D+ CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+/-\u003c/sup\u003e, CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e+/-\u003c/sup\u003e, and CD56\u003csup\u003e-\u003c/sup\u003eCD16\u003csup\u003e+\u003c/sup\u003e NK cell populations grouped by UPDRS score (\u0026lt;20, 20-32, 32+). (D-E) Plots show frequency of NKG2D+ CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+/-\u003c/sup\u003e subpopulations and CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e+/- \u003c/sup\u003esubpopulations grouped by UPDRS score. (F, G, H) Plots show frequency of NKG2A+ CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+/-\u003c/sup\u003e, CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e+/-\u003c/sup\u003e, and CD56\u003csup\u003e-\u003c/sup\u003eCD16\u003csup\u003e+\u003c/sup\u003e NK cell populations grouped by UPDRS score. (I, J) Plots show frequency of NKG2A+ CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+/-\u003c/sup\u003e subpopulations and CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e+/-\u003c/sup\u003e subpopulations grouped by UPDRS score. (K, L, M) Plots show frequency of CX3CR1+ CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+/-\u003c/sup\u003e, CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e+/-\u003c/sup\u003e, and CD56\u003csup\u003e-\u003c/sup\u003eCD16\u003csup\u003e+\u003c/sup\u003e NK cell populations grouped by UPDRS score. (N, O) Plots show frequency of CX3CR1+ CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+/-\u003c/sup\u003e subpopulations and CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e+/-\u003c/sup\u003e subpopulations grouped by UPDRS score. Aggregate NK cell population data were analyzed by one-way ANOVA followed by Tukey’s post hoc analysis and subpopulation data were analyzed by two-way ANOVA followed by Tukey’s post hoc analysis. Data represent mean ± SEM. *\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, ***\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001, ****\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.0001.\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-1883506/v1/89d8f83ed209b5131f111783.png"},{"id":25000746,"identity":"46e42613-e205-449e-a738-fa2d96459eaf","added_by":"auto","created_at":"2022-08-09 17:59:15","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":82173,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExpression of NKG2D is increased in CD56\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ebright\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003eCD16\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e+\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e NK cells in PD groups with UPDRS score \u0026lt;32.\u003c/strong\u003e (A, B, C) Graphs show MFI of NKG2D+ CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+/-\u003c/sup\u003e, CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e+/-\u003c/sup\u003e, and CD56\u003csup\u003e-\u003c/sup\u003eCD16\u003csup\u003e+\u003c/sup\u003e NK cell populations grouped by UPDRS score (\u0026lt;20, 20-32, 32+). (D, E) Plots show MFI of NKG2D+ CD56\u003csup\u003ebright\u003c/sup\u003e subpopulations and CD56\u003csup\u003edim\u003c/sup\u003e subpopulations grouped by UPDRS score. (F, G, H) Plots show MFI of NKG2A+ CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+/-\u003c/sup\u003e, CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e+/-\u003c/sup\u003e, and CD56\u003csup\u003e-\u003c/sup\u003eCD16\u003csup\u003e+\u003c/sup\u003e NK cell populations grouped by UPDRS score. (I, J) Plots show MFI of NKG2A+ CD56\u003csup\u003ebright\u003c/sup\u003e subpopulations and CD56\u003csup\u003edim\u003c/sup\u003e subpopulations grouped by UPDRS score. (K, L, M) Plots show MFI of CX3CR1+ CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+/-\u003c/sup\u003e, CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e+/-\u003c/sup\u003e, and CD56\u003csup\u003e-\u003c/sup\u003eCD16\u003csup\u003e+\u003c/sup\u003e NK cell populations grouped by UPDRS score. (N, O) Plots show MFI of CX3CR1+ CD56\u003csup\u003ebright\u003c/sup\u003e subpopulations and CD56\u003csup\u003edim\u003c/sup\u003e subpopulations grouped by UPDRS score. Aggregate NK cell population data were analyzed by one-way ANOVA followed by Tukey’s post hoc analysis and subpopulation data were analyzed by two-way ANOVA followed by Tukey’s post hoc analysis. Data represent mean ± SEM. *\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, ***\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001, ****\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.0001.\u003c/p\u003e","description":"","filename":"Fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-1883506/v1/c5021422adf2b8d885443080.png"},{"id":25000745,"identity":"817bc447-c8c0-4e43-a22c-4b36c298fa20","added_by":"auto","created_at":"2022-08-09 17:59:15","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":28044,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFrequency of CD56\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003edim\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e NK cell subpopulations vary despite disease duration. \u003c/strong\u003ePlots show frequency of total NK cells of CD56\u003csup\u003ebright\u003c/sup\u003e subpopulations (A), CD56\u003csup\u003edim\u003c/sup\u003e subpopulations (B), and CD56\u003csup\u003e-\u003c/sup\u003eCD16\u003csup\u003e+\u003c/sup\u003e (C) from HC and PD samples stratified by disease duration (\u0026lt;5 years, 5-10 years, 10+ years). Data were analyzed by two-way ANOVA followed by Tukey’s post hoc analysis. Data represent mean ± SEM. *\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, ***\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001, ****\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.0001.\u003c/p\u003e","description":"","filename":"Fig5.png","url":"https://assets-eu.researchsquare.com/files/rs-1883506/v1/44cb2e25a54c63e200d11554.png"},{"id":25001572,"identity":"02e1c390-fdb8-4c9a-b316-1d0e4da91195","added_by":"auto","created_at":"2022-08-09 18:04:15","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":91976,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIncreased\u003c/strong\u003e \u003cstrong\u003efrequency of NKG2A in CD56\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ebright\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e NK\u003c/strong\u003e \u003cstrong\u003ecells observed with longer disease duration. \u003c/strong\u003e(A, B, C) Plots show frequency of NKG2D+ CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+/-\u003c/sup\u003e, CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e+/-\u003c/sup\u003e, and CD56\u003csup\u003e-\u003c/sup\u003eCD16\u003csup\u003e+\u003c/sup\u003e NK cell populations grouped by disease duration (\u0026lt;5 years, 5-10 years, 10+ years). (D, E) Plots show frequency of NKG2D+ CD56\u003csup\u003ebright\u003c/sup\u003e subpopulations and CD56\u003csup\u003edim\u003c/sup\u003e subpopulations grouped by disease duration. (F, G, H) Plots show frequency of NKG2A+ CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+/-\u003c/sup\u003e, CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e+/-\u003c/sup\u003e, and CD56\u003csup\u003e-\u003c/sup\u003eCD16\u003csup\u003e+ \u003c/sup\u003eNK cell populations grouped by disease duration. (I, J) Plots show frequency of NKG2A+ CD56\u003csup\u003ebright\u003c/sup\u003e subpopulations and CD56\u003csup\u003edim\u003c/sup\u003e subpopulations grouped by disease duration. (K, L, M) Plots show frequency of CX3CR1+ CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+/-\u003c/sup\u003e, CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e+/-\u003c/sup\u003e, and CD56\u003csup\u003e-\u003c/sup\u003eCD16\u003csup\u003e+ \u003c/sup\u003eNK cell populations grouped by disease duration. (N, O) Plots show frequency of CX3CR1+ CD56\u003csup\u003ebright\u003c/sup\u003e subpopulations and CD56\u003csup\u003edim\u003c/sup\u003e subpopulations grouped by disease duration. Aggregate NK cell population data were analyzed by one-way ANOVA followed by Tukey’s post hoc analysis and subpopulation data were analyzed by two-way ANOVA followed by Tukey’s post hoc analysis. Data represent mean ± SEM. *\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, ***\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001, ****\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.0001.\u003c/p\u003e","description":"","filename":"Fig6.png","url":"https://assets-eu.researchsquare.com/files/rs-1883506/v1/0a2ca748073fdd631db90982.png"},{"id":25001571,"identity":"6f00aff2-2e2f-40ce-8456-50d80d9be115","added_by":"auto","created_at":"2022-08-09 18:04:15","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":88393,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExpression of NKG2D is increased in CD56\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ebright\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e and CD56\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003edim\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e NK cells\u003c/strong\u003e \u003cstrong\u003ewith longer PD disease duration. \u003c/strong\u003e(A, B, C) Graphs show MFI of NKG2D+ CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+/-\u003c/sup\u003e, CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e+/-\u003c/sup\u003e, and CD56\u003csup\u003e-\u003c/sup\u003eCD16\u003csup\u003e+\u003c/sup\u003e NK cell populations grouped by disease duration (\u0026lt;5 years, 5-10 years, 10+ years). (D, E) Plots show MFI of NKG2D+ CD56\u003csup\u003ebright\u003c/sup\u003e subpopulations and CD56\u003csup\u003edim\u003c/sup\u003e subpopulations grouped by disease duration. (F, G, H) Plots show MFI of NKG2A+ CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+/-\u003c/sup\u003e, CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e+/-\u003c/sup\u003e, and CD56\u003csup\u003e-\u003c/sup\u003eCD16\u003csup\u003e+\u003c/sup\u003e NK cell populations grouped by disease duration. (I, J) Plots show MFI of NKG2A+ CD56\u003csup\u003ebright\u003c/sup\u003e subpopulations and CD56\u003csup\u003edim\u003c/sup\u003e subpopulations grouped by disease duration. (K, L, M) Plots show MFI of CX3CR1+ CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+/-\u003c/sup\u003e, CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e+/-\u003c/sup\u003e, and CD56\u003csup\u003e-\u003c/sup\u003eCD16\u003csup\u003e+ \u003c/sup\u003eNK cell populations grouped by disease duration. (N, O) Plots show MFI of CX3CR1+ CD56\u003csup\u003ebright\u003c/sup\u003e subpopulations and CD56\u003csup\u003edim\u003c/sup\u003e subpopulations grouped by disease duration. Aggregate NK cell population data were analyzed by one-way ANOVA followed by Tukey’s post hoc analysis and subpopulation data were analyzed by two-way ANOVA followed by Tukey’s post hoc analysis. Data represent mean ± SEM. *\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, ***\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001, ****\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.0001.\u003c/p\u003e","description":"","filename":"Fig7.png","url":"https://assets-eu.researchsquare.com/files/rs-1883506/v1/8462d5ee3e422c6597cca1e5.png"},{"id":51216799,"identity":"21050aae-e6ad-4771-9138-2a00c8197568","added_by":"auto","created_at":"2024-02-16 08:12:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1901663,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1883506/v1/766a2a11-1cef-4897-8b02-b329c880ecc8.pdf"}],"financialInterests":"(Not answered)","formattedTitle":"Distinctive blood CD56\u003csup\u003ebright\u003c/sup\u003e NK cell subset profile and increased NKG2D expression in CD56\u003csup\u003ebright\u003c/sup\u003e NK cells in Parkinson’s disease","fulltext":[{"header":"Introduction","content":"\u003cp\u003eRecent evidence has implicated the role of neuroinflammation (thoroughly reviewed in \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e) in PD pathogenesis. Moreover, changes in peripheral immune cell distributions have been documented in PD patients \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Of particular interest are natural killer (NK) cells, an innate immune system population, traditionally associated with the destruction of malignant cells following signaling through activating and inhibitory receptors resulting in cytotoxicity mediated via perforin and granzyme \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. A recent study utilizing the preformed fibril (PFF) α-syn mouse model of PD demonstrated infiltration of NK cell in the central nervous system (CNS) and altered frequency and numbers in the periphery 5 months post-injection \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Furthermore, NK cells were shown to internalize and degrade α-syn aggregates and systemic depletion of NK cells in a preclinical mouse model of PD exacerbated synuclein pathology and motor symptoms, further implicating NK cells as a relevant cell type in PD pathogenesis \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Recent work in a murine model showed that NK cell numbers declined and showed functional deficits in α-syn clearance with age, highlighting the necessity for further characterization of NK cells in PD patients to elucidate profile differences \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Interestingly, studies have found increased total NK cell numbers in PD patients compared to non-PD controls \u003csup\u003e2,3,9\u0026minus;12\u003c/sup\u003e highlighting a key opportunity to explore NK cells as a biomarker for PD.\u003c/p\u003e \u003cp\u003eHuman NK cells have historically been broadly classified by their expression of cell surface markers, cluster of differentiation (CD) 56 (neural cell adhesion molecule) and CD16 (Fcγ Receptor III) and being CD3 negative. Distinct NK cell subpopulations in humans have been identified based on variable expression of CD56 and CD16: CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e\u0026minus;\u003c/sup\u003e, CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003edim\u003c/sup\u003e, CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e\u0026minus;\u003c/sup\u003e, CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003ebright\u003c/sup\u003e, and CD56\u003csup\u003e\u0026minus;\u003c/sup\u003eCD16\u003csup\u003ebright \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. The majority, upwards of 90%, of blood circulating NK cells are CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e+/\u0026minus;\u003c/sup\u003e with the remainder being predominantly CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003edim/\u0026minus;\u003c/sup\u003e and the smallest minority being CD56\u003csup\u003e\u0026minus;\u003c/sup\u003eCD16\u003csup\u003ebright \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. It remains actively debated the developmental progression for NK cell expression of CD56, but many consider the CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003edim/\u0026minus;\u003c/sup\u003e population as the precursor to CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003ebright\u003c/sup\u003e populations. CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003edim/\u0026minus;\u003c/sup\u003e are abundant cytokine producers while CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003ebright\u003c/sup\u003e are the predominant cytotoxic population \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn addition to expression of CD56 and CD16, differential expressions of activating and inhibitory receptors are shown to mediate NK cell activity \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. The cumulative sum of activating and inhibitory signaling directly regulates NK cell effector functions, such as cytotoxicity. Natural killer group 2D (NKG2D) recepter is an activating receptor constitutively expressed on NK cells \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Alterations in NKG2D have previously been reported in PD patients (summarized in \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e)The frequency of NKG2D\u0026thinsp;+\u0026thinsp;NK cells have been reported to be unchanged \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e and increased in PD patient samples compared to healthy controls \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Natural killer group 2A (NKG2A) receptor is an inhibitory receptor expressed by NK cells that recognizes histocompatibility antigen, alpha chain E (HLA-E), also known as major histocompatibility complex (MHC) class I antigen E. NKG2A\u0026thinsp;+\u0026thinsp;NK cells have previously been reported to be decreased in PD patients compared to controls \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. The interaction between chemokine C-X3-C motif receptor 1 (CX3CR1) and its ligand CX3CL1 (also known as fractalkine) mediates immune cell chemotaxis \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Expression of CX3CR1 has been shown to be essential for NK cell homing to the CNS and ameliorating disease in an experimental autoimmune encephalomyelitis (EAE) model of multiple sclerosis \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. As NK cells have been demonstrated to be present in brains of patients with synucleinopathies and in mouse models of PD \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e, assessing CX3CR1 expression in PD patients warrants further investigation.\u003c/p\u003e \u003cp\u003eDiscovery of distinct immune cell receptor profiles representing early diagnostic biomarkers provides an opportunity for earlier intervention and treatment. To date, a comprehensive analysis of NK subpopulations and their variable expression of activating and inhibitory receptors in PD has not been carried out. Here we analyzed the frequency and expression intensity of NK receptors, NKG2D, NKG2A and CX3CR1, by NK subsets and parsed NK subsets into 6 NK subpopulations to resolve additional NK cell profile differences. Peripheral blood samples of 71 donors (36 PD, 35 HC) were analyzed by conventional flow cytometry. Using mean fluorescence intensity (MFI), we evaluated the variable expression of markers of interest to quantify distinct profiles representing differences between HC and PD samples. We used the total score of Unified Parkinson\u0026rsquo;s Disease Rating Scale (UPDRS) part III and PD duration to stratify the differences across NK cell subpopulations.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eNK Cell Frequency is Comparable between PD and Healthy Control\u003c/h2\u003e \u003cp\u003eHistorically, NK cell populations have been aggregated along variable expressions of CD56: CD56\u003csup\u003ebright\u003c/sup\u003e, CD56\u003csup\u003edim\u003c/sup\u003e and, the rarely included, CD56\u003csup\u003e\u0026minus;\u003c/sup\u003e. Here we included NK subset population outcomes and expanded analysis utilizing six subpopulations based on CD56 and CD16 expression defined previously \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Cryopreserved peripheral blood mononuclear cells (PBMCs) from 71 donors, (36 PD, 35 HC; \u003cb\u003eTable\u0026nbsp;1\u003c/b\u003e) were thawed and processed for flow cytometry analysis. Using our 10-parameter panel we investigated six NK cell subpopulations: (1) CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e\u0026minus;\u003c/sup\u003e, (2) CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003edim\u003c/sup\u003e, (3) CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e\u0026minus;\u003c/sup\u003e, (4) CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003edim\u003c/sup\u003e, (5) CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003ebright\u003c/sup\u003e, and (6) CD56\u003csup\u003e\u0026minus;\u003c/sup\u003eCD16\u003csup\u003e+\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). Population gates were established using quantitatively determined antibody titrations, gates set using single color and fluorescence minus one (FMO) control, and compensation to reduce fluorescent spill-over. Only live single cell populations were analyzed, to prevent non-specific binding artifacts or misrepresentation due to doublets.\u003c/p\u003e \u003cp\u003eThe frequencies of cells expressing CD45\u003csup\u003e+\u003c/sup\u003e (hematopoietic), CD3\u003csup\u003e+\u003c/sup\u003e (T cells), CD3\u003csup\u003e\u0026minus;\u003c/sup\u003eCD14\u003csup\u003e+\u003c/sup\u003eCD19\u003csup\u003e+\u003c/sup\u003e (B cells/monocytes), and CD3\u003csup\u003e\u0026minus;\u003c/sup\u003eCD14\u003csup\u003e\u0026minus;\u003c/sup\u003eCD19\u003csup\u003e\u0026minus;\u003c/sup\u003e (NK cells) were not significantly different between PD or HC (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). In alignment with previous literature assessing NK cell subsets in PBMCs, we quantified CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+/\u0026minus;\u003c/sup\u003e, CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e+/\u0026minus;\u003c/sup\u003e, and CD56\u003csup\u003e\u0026minus;\u003c/sup\u003eCD16\u003csup\u003e+\u003c/sup\u003e NK cell frequencies and found no significant differences between PD or HC (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eFrequency of NKG2D\u0026thinsp;+\u0026thinsp;CD56\u003csup\u003ebright\u003c/sup\u003e NK cells increased with higher UPDRS III scores\u003c/h2\u003e \u003cp\u003eTo date, differences that may exist in the activating and inhibitory receptor profiles in NK cell populations as PD motor severity increases have yet to be defined. We began by stratifying PD samples into three groups based on the severity of their motor symptoms using the UPDRS-III as a marker of severity. A score of \u0026lt;\u0026thinsp;20 corresponds with mild motor symptoms, 20\u0026ndash;32 with moderate motor symptoms, and 32\u0026thinsp;+\u0026thinsp;with severe motor symptoms and examined differences in the frequency of NK cells by subpopulations, and their expression of NKG2D, NKG2A and CX3CR1 were assessed.\u003c/p\u003e \u003cp\u003eWhile differences in aggregate populations in PD have been identified previously \u003csup\u003e2,3,9\u0026minus;12\u003c/sup\u003e, we sought to further characterize the spectrum of changes that may exist across NK cell populations in relation to UPDRS III motor scores. Through analysis of CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+/\u0026minus;\u003c/sup\u003e NK cell subpopulations we found a significantly lower frequency of CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+\u003c/sup\u003e than CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e\u0026minus;\u003c/sup\u003e NK cells in HC (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) compared to patients with UPDRS\u0026thinsp;\u0026lt;\u0026thinsp;20 (p\u0026thinsp;=\u0026thinsp;0.023), while UPDRS\u0026thinsp;\u0026gt;\u0026thinsp;20 lacked this difference (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Within the CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e+/\u0026minus;\u003c/sup\u003e NK cell subpopulations, HC samples showed a significantly lower frequency of CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e\u0026minus;\u003c/sup\u003e NK cells compared to CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003edim\u003c/sup\u003e NK cells (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003ebright\u003c/sup\u003e NK cells (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). In the UPDRS 32\u0026thinsp;+\u0026thinsp;group a significantly lower frequency of CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e\u0026minus;\u003c/sup\u003e NK cells compared to CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003edim\u003c/sup\u003e (p\u0026thinsp;=\u0026thinsp;0.0052) and CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003ebright\u003c/sup\u003e NK (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) was observed (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Additionally, the frequency of CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003ebright\u003c/sup\u003e NK cells was significantly less in the UPDRS\u0026thinsp;\u0026lt;\u0026thinsp;20 group than in the UPDRS 20\u0026ndash;32 group (p\u0026thinsp;=\u0026thinsp;0.0323). The UPDRS 20\u0026ndash;32 group showed a significant increase in frequency of the CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003ebright\u003c/sup\u003e subpopulation compared to the CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e\u0026minus;\u003c/sup\u003e (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003edim\u003c/sup\u003e (p\u0026thinsp;=\u0026thinsp;0.0009) NK cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). No significant differences were observed in the CD56\u003csup\u003e\u0026minus;\u003c/sup\u003eCD16\u003csup\u003e+\u003c/sup\u003e NK cell population across UPDRS III score groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003eThe overactivation of NK populations via activating receptors represents a potential explanation for the sustained and progressive neuroinflammation in PD, herein we assessed alterations in the frequency of NKG2D, an activating receptor, on NK cell populations in relation to UPDRS III scores.\u003c/p\u003e \u003cp\u003eAssessment of CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+/\u0026minus;\u003c/sup\u003e NK cell subset showed the frequency of activating receptor NKG2D was significantly increased in UPDRS 20\u0026ndash;32 (p\u0026thinsp;=\u0026thinsp;0.0153) and UPDRS 32+ (p\u0026thinsp;=\u0026thinsp;0.0489) compared to samples from participants with UPDRS scores\u0026thinsp;\u0026lt;\u0026thinsp;20 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). No significant differences in frequencies of NKG2D\u0026thinsp;+\u0026thinsp;cells were observed in the CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e+/\u0026minus;\u003c/sup\u003e or CD56\u003csup\u003e\u0026minus;\u003c/sup\u003eCD16\u003csup\u003e+\u003c/sup\u003e NK cell subsets (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB-C). Further stratification of the CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+/\u0026minus;\u003c/sup\u003e NK cells into CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+\u003c/sup\u003e and CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e\u0026minus;\u003c/sup\u003e NK cell subpopulations revealed a significant decrease in NKG2D in the CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e\u0026minus;\u003c/sup\u003e versus the CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+\u003c/sup\u003e NK cells in samples with UPDRS scores\u0026thinsp;\u0026lt;\u0026thinsp;20 (p\u0026thinsp;=\u0026thinsp;0.0026) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). Across all HC and PD groups, a significant increase in NKG2D frequency was observed when comparing CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e\u0026minus;\u003c/sup\u003e and CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003edim\u003c/sup\u003e NK cells to CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003ebright\u003c/sup\u003e NK cells, with the highest frequency of NKG2D observed in the CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003ebright\u003c/sup\u003e NK cells (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE). Interestingly, in HC there was a significant increase in NKG2D frequency in CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003edim\u003c/sup\u003e NK cells compared to the CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e\u0026minus;\u003c/sup\u003e NK cells (p\u0026thinsp;=\u0026thinsp;0.0015) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE). This difference was not observed in the remaining PD groups.\u003c/p\u003e \u003cp\u003eConversely to the potential action of NKG2D, changes to inhibitory receptor NKG2A represent an alternative mechanism of change for NK cell function that may slow PD progression. Analysis of the frequency of NKG2A\u0026thinsp;+\u0026thinsp;cells across UPDRS scores showed no significant differences between aggregate NK cell subsets (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF-H). Additionally, investigation of CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+/\u0026minus;\u003c/sup\u003e NK cell subpopulations showed no significant differences in frequency of NKG2A across UPDRS scores (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eI). However, a significant decrease in NKG2A frequency was observed in CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003ebright\u003c/sup\u003e NK cells compared to CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e\u0026minus;\u003c/sup\u003e NK cells in both HC and UPDRS score 20\u0026ndash;32 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eJ).\u003c/p\u003e \u003cp\u003eAlterations to activation and inhibitory receptor profiles on NK cells may not represent the entirety of contributing factors in PD severity progression. Aberrant homing of NK cells to the brain may underlie increased risk of cytotoxicity to dopamine (DA) neurons. To understand this, we investigated NK homing receptor CX3CR1, which has been found to guide NK cells to the brain. Our results showed no significant differences in CX3CR1 frequency across NK subsets (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eK-M) or within CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+/\u0026minus;\u003c/sup\u003e NK cell subpopulations (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eN). In the CD56\u003csup\u003edim\u003c/sup\u003e NK cell subpopulations, HC had a significantly greater frequency of CX3CR1 on CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003edim\u003c/sup\u003e (p\u0026thinsp;=\u0026thinsp;0.0002) and CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003ebright\u003c/sup\u003e (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) NK cells than CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e\u0026minus;\u003c/sup\u003e NK cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eO). PD groups UPDRS\u0026thinsp;\u0026lt;\u0026thinsp;20 and 20\u0026ndash;32 also had a significant increase in the frequency of CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003ebright\u003c/sup\u003e NK cells compared to CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e\u0026minus;\u003c/sup\u003e NK cells (p\u0026thinsp;=\u0026thinsp;0.0196 and p\u0026thinsp;=\u0026thinsp;0.0262, respectively) observed in HC samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eO).\u003c/p\u003e \u003cp\u003e \u003cb\u003eExpression of NKG2D is increased in CD56\u003c/b\u003e \u003csup\u003e \u003cb\u003ebright\u003c/b\u003e \u003c/sup\u003e \u003cb\u003eCD16\u003c/b\u003e \u003csup\u003e \u003cb\u003e+\u003c/b\u003e \u003c/sup\u003e \u003cb\u003eNK cells in PD groups with UPDRS score\u0026thinsp;\u0026lt;\u0026thinsp;32\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe binary presence or absence, or frequency, of a receptor on NK cells may not provide the depth of detail necessary to understand changes at the receptor level; therefore, to aptly reflect the potential bias towards activation or inhibition, we assessed the mean fluorescence intensity (MFI) to evaluate the variability in expression intensity of receptors in NK cell profiles. We found a significant increase in NKG2D expression on CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+/\u0026minus;\u003c/sup\u003e NK cells with a UPDRS score 20\u0026ndash;32 compared to UPDRS score\u0026thinsp;\u0026lt;\u0026thinsp;20 (p\u0026thinsp;=\u0026thinsp;0.0287) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). No significant differences were observed in the MFI of NKG2D or NKG2A for the remainder of NK subsets (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB-C). We observed a significant increase in the expression of NKG2D in the CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+\u003c/sup\u003e NK cell subpopulation compared to the CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e\u0026minus;\u003c/sup\u003e NK cells in UPDRS\u0026thinsp;\u0026lt;\u0026thinsp;20 (p\u0026thinsp;=\u0026thinsp;0.023) and 20\u0026ndash;32 (p\u0026thinsp;=\u0026thinsp;0.041) groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD). The CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003ebright\u003c/sup\u003e NK cells displayed significantly increased expression of NKG2D compared to the CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e\u0026minus;\u003c/sup\u003e and CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003edim\u003c/sup\u003e NK cells, and this was conserved across HC and PD groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE). No significant differences were observed in expression of NKG2A for NK subsets or NK subpopulations (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF-J). Lastly, assessment of CX3CR1 expression showed no significant changes across NK cell subsets or subpopulations (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eK-O).\u003c/p\u003e \u003cp\u003e \u003cb\u003eIncreased frequency of NKG2A in CD56\u003c/b\u003e \u003csup\u003e \u003cb\u003ebright\u003c/b\u003e \u003c/sup\u003e \u003cb\u003eNK cells observed with longer disease duration.\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo assess changes that may correlate with different stages of PD we subdivided PD patients into three groups according to the disease duration at sampling: \u0026lt;5yrs (early), 5-10yrs (intermediate), 10\u0026thinsp;+\u0026thinsp;yrs (late) and investigated the frequency of NKG2D, NKG2A and CX3CR1 across NK cell populations\u003c/p\u003e \u003cp\u003eTotal NK cell frequency evaluation showed a significantly reduced CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+\u003c/sup\u003e NK cell subpopulation compared to CD56\u003csup\u003e+\u003c/sup\u003eCD16\u003csup\u003e\u0026minus;\u003c/sup\u003e NK cells in HC (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) but not PD (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). In CD56\u003csup\u003edim\u003c/sup\u003e NK cells, the CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003ebright\u003c/sup\u003e NK cells showed a significantly greater frequency compared to CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e\u0026minus;\u003c/sup\u003e NK cells in HC (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), PD\u0026thinsp;\u0026lt;\u0026thinsp;5yrs (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), 5-10yrs (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), and 10\u0026thinsp;+\u0026thinsp;yrs (p\u0026thinsp;=\u0026thinsp;0.031) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). Interestingly, a significantly greater frequency of CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003edim\u003c/sup\u003e NK cells compared to CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e\u0026minus;\u003c/sup\u003e NK cells was observed in HC (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and PD durations\u0026thinsp;\u0026lt;\u0026thinsp;5yrs (p\u0026thinsp;=\u0026thinsp;0.017) and 5-10yrs (p\u0026thinsp;=\u0026thinsp;0.0494); however, this was not present in samples with a PD duration 10\u0026thinsp;+\u0026thinsp;yrs (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). Additionally, in samples with PD duration\u0026thinsp;\u0026lt;\u0026thinsp;5yrs, a significantly greater frequency of CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003ebright\u003c/sup\u003e NK cells was observed compared to CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003edim\u003c/sup\u003e NK cells (p\u0026thinsp;=\u0026thinsp;0.001) which was not present in HC or other PD groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). No differences in the CD56\u003csup\u003e\u0026minus;\u003c/sup\u003e NK cell population were observed across HC and PD groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003eWe assessed differences in NK population frequencies for both subsets and subpopulations for activating receptor NKG2D, inhibitory receptor NKG2A, and homing receptor CX3CR1. We found no significant differences in NKG2D (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA-C) expression frequency in NK subsets when clustered by disease duration. Conversely, we observed a significantly reduced frequency of NKG2D expression in the CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e\u0026minus;\u003c/sup\u003e NK cells compared to the CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+\u003c/sup\u003e NK cells at \u0026lt;\u0026thinsp;5yrs PD duration (p\u0026thinsp;=\u0026thinsp;0.002) that was not present in HC or other PD duration groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD). Strikingly, in HC a significantly increased NKG2D frequency was observed in the CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003edim\u003c/sup\u003e NK cells compared to the CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e\u0026minus;\u003c/sup\u003e NK cells (p\u0026thinsp;=\u0026thinsp;0.001) that was not observed in PD groups; however, all groups showed a significantly higher NGK2D frequency in the CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003edim\u003c/sup\u003e and CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003ebright\u003c/sup\u003e NK cells compared to the CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e\u0026minus;\u003c/sup\u003e NK cells (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE).\u003c/p\u003e \u003cp\u003eWe found a significantly greater frequency of NKG2A in the CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+/\u0026minus;\u003c/sup\u003e subset in the group with 10\u0026thinsp;+\u0026thinsp;yrs PD duration compared to the group with \u0026lt;\u0026thinsp;5yrs of PD duration (p\u0026thinsp;=\u0026thinsp;0.025) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eF) but no significant differences in CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e+/\u0026minus;\u003c/sup\u003e or CD56\u003csup\u003e\u0026minus;\u003c/sup\u003eCD16\u003csup\u003e+/\u0026minus;\u003c/sup\u003e NK cell subsets (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eG-H). Analysis of NK subpopulations showed no significant changes in CD56\u003csup\u003ebright\u003c/sup\u003e subpopulations (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eI); however, a significant reduction in NKG2A frequency of CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003ebright\u003c/sup\u003e NK cells compared to CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e\u0026minus;\u003c/sup\u003e NK cells were observed in HC (p\u0026thinsp;=\u0026thinsp;0.0005) and 10\u0026thinsp;+\u0026thinsp;yrs PD duration (p\u0026thinsp;=\u0026thinsp;0.023) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eJ).\u003c/p\u003e \u003cp\u003eNo significant differences in expression frequency of CX3CR1 were observed in NK subsets (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eK-M) or in CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+/\u0026minus;\u003c/sup\u003e NK cell subpopulations (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eN). Conversely, HC (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), \u0026lt;5yrs (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), and 5-10yrs (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0002) PD duration groups showed a significantly greater CX3CR1 frequency in the CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003ebright\u003c/sup\u003e NK cells in comparison to the CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e\u0026minus;\u003c/sup\u003e NK cells, but this was absent in PD group 10\u0026thinsp;+\u0026thinsp;yrs (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eO). Interestingly, HC (p\u0026thinsp;=\u0026thinsp;0.002) and the 5-10yrs PD duration group (p\u0026thinsp;=\u0026thinsp;0.0008) had a significantly lower CX3CR1 frequency in the CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e\u0026minus;\u003c/sup\u003e population compared to CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003edim\u003c/sup\u003e population but this was not present in PD groups\u0026thinsp;\u0026lt;\u0026thinsp;5 yrs or 10\u0026thinsp;+\u0026thinsp;yrs (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eO). Furthermore, the CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e\u0026minus;\u003c/sup\u003e NK cells from PD group 5-10yrs showed a significantly higher frequency of CX3CR1 than the same population from the PD group 10\u0026thinsp;+\u0026thinsp;yrs (p\u0026thinsp;=\u0026thinsp;0.044) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eO).\u003c/p\u003e \u003cp\u003e \u003cb\u003eExpression of NKG2D is increased in CD56\u003c/b\u003e \u003csup\u003e \u003cb\u003ebright\u003c/b\u003e \u003c/sup\u003e \u003cb\u003eand CD56\u003c/b\u003e\u003csup\u003e\u003cb\u003edim\u003c/b\u003e\u003c/sup\u003e \u003cb\u003eNK cells with longer PD disease duration.\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo address distinctive changes in receptor expression we included analysis of expression measured by MFI to ensure a robust understanding of the receptor profiles within these populations over time in PD. The expression of activating receptor, NKG2D, showed no significant difference in the CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+/\u0026minus;\u003c/sup\u003e NK cell subset (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA) but was found to be significantly greater in the CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e+/\u0026minus;\u003c/sup\u003e NK cell subset in PD 5-10yrs versus HC (p\u0026thinsp;=\u0026thinsp;0.045) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB). CD56\u003csup\u003e\u0026minus;\u003c/sup\u003e NK cell subset showed no significant difference in expression of NKG2D (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eC). Importantly, analysis of subpopulations revealed that all PD groups had a significantly greater expression of NKG2D in CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+\u003c/sup\u003e NK cells compared to HC (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eD). Additionally, PD\u0026thinsp;\u0026lt;\u0026thinsp;5yrs (p\u0026thinsp;=\u0026thinsp;0.0001), PD 5-10yrs (p\u0026thinsp;=\u0026thinsp;0.002), and PD 10\u0026thinsp;+\u0026thinsp;yrs (p\u0026thinsp;=\u0026thinsp;0.033) had a significantly greater expression of NKG2D on CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+\u003c/sup\u003e NK cells compared to CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e\u0026minus;\u003c/sup\u003e NK cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eD). We observed significantly greater expression of NKG2D on CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003ebright\u003c/sup\u003e NK cells compared to CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e\u0026minus;\u003c/sup\u003e NK cells in all groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eE). Significantly increased expression of NKG2D on CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003ebright\u003c/sup\u003e NK cells compared to CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003edim\u003c/sup\u003e NK cells was observed across HC, PD\u0026thinsp;\u0026lt;\u0026thinsp;5yrs, 5-10yrs (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and 10\u0026thinsp;+\u0026thinsp;yrs (p\u0026thinsp;=\u0026thinsp;0.0004) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eE). Inhibitory receptor NKG2A was found to have a significantly greater expression in the CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+/\u0026minus;\u003c/sup\u003e NK cell subset at PD 5-10yrs compared to PD\u0026thinsp;\u0026lt;\u0026thinsp;5yrs (p\u0026thinsp;=\u0026thinsp;0.045) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eF). No other significant differences in MFI were observed for NKG2A (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eG-J). No significant differences in the expression of CX3CR1 were observed (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eK-O).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003ePreviously, analysis of NK populations in PD has been done using NK cell subset analysis based on variable expression of CD56 and CD16, with minimal inclusion of CD56\u003csup\u003e\u0026minus;\u003c/sup\u003e. Here we show, defining NK cell profiles with granular and functional subpopulations allows for deeper understanding of changes within NK populations in PD. Analysis of expression frequency and MFI within each group to assess receptors NKG2D, NKG2A and CX3CR1, enabled us to outline a profile for the subtle changes within these NK cell populations.\u003c/p\u003e \u003cp\u003eWhile our results show no significant difference in the frequency of NK cells between HC and PD patients using CD56 and CD16 \u003csup\u003e2,12\u003c/sup\u003e, this is unsurprising as the statistical significance may be absent due to our reduced population size for both PD and HC. However, our NK cell population frequencies for both PD and HC align with previous findings \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Additionally, our results corroborate previous findings on receptor expression profiles within aggregate NK populations, such as the variable expression of NKG2D, NKG2A, and CX3CR1 on CD56\u003csup\u003ebright\u003c/sup\u003e, CD56\u003csup\u003edim\u003c/sup\u003e, and CD56\u003csup\u003e\u0026minus;\u003c/sup\u003e NK subsets \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Understanding of the relationship between these NK receptors over the course of PD facilitates establishment of disease profiles that can inform the role of NK cells in PD along with enabling development of clinical treatment options.\u003c/p\u003e \u003cp\u003eNuanced NK cell subpopulation profiles are a necessity for parsing key differences that may exist in PD progression, with these defined profiles insights on biomarkers that can be used to classify critical windows for intervention may be uncovered. To accomplish this, we assessed NKG2D and NKG2A in an effort to define the involvement of activating and inhibitory signaling, respectively, that underlie immune context changes that can inform understanding of PD progression and severity. NK populations exhibit distinct functional differences based on the binary presence or absence in conjunction with the expression intensity of a repertoire of receptors, meriting the necessity to define differences that may reflect important profile changes. These differences may represent readily observable biomarker changes in these variable populations over the course of disease that can inform treatment and diagnosis. Our analysis shows significant changes within CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+/\u0026minus;\u003c/sup\u003e and CD56\u003csup\u003edim\u003c/sup\u003eCD16\u003csup\u003e+/\u0026minus;\u003c/sup\u003e populations with respect to the frequency of NKG2D and NKG2A, offering valuable insight into the immunomodulatory and cytotoxicity context that NK cells may mediate in PD patients.\u003c/p\u003e \u003cp\u003eMost importantly, we show the CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+/\u0026minus;\u003c/sup\u003e NK cell subset and subpopulations have increased NKG2D frequency and expression, suggesting an increased activation potential for the CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+/\u0026minus;\u003c/sup\u003e NK cell subset in PD patients. With the CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+/\u0026minus;\u003c/sup\u003e NK cell subset traditionally attributed with a primary role as immunomodulators via cytokine production and release \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e, the increased activation of this population may correlate with changes in immune activity underlying changes in disease severity. Interestingly, we also found a significant increase in NKG2D expression as PD duration increased compared to HC in CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+\u003c/sup\u003e, suggesting a potential increase in activation potential for this population compared to HC. Taken together these findings highlight that CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+\u003c/sup\u003e NK population overactivation in PD may correlate with increases in pathology. In conjunction with our findings that no significant increases in NKG2A expression were discovered, there may be a disproportionate increase in activation signaling via NKG2D on NK cells in patients with PD, resulting in a pathological change that requires further investigation to define the role this change has in PD patients. Further understanding of the impact that increased activation receptor frequency and expression has in the interplay between NK cells and adjacent immune cell populations may provide clarity on the role NK cells have in altering the immune landscape. Defining this relationship enables development of targeted interventions to alter the immune context underlying PD progression.\u003c/p\u003e"},{"header":"Materials And Methods","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eSamples\u003c/h2\u003e \u003cp\u003ePBMC samples were collected in sodium citrate-coated tubes following ficoll gradient separation, suspended in dimethyl sulfoxide (DMSO) cryopreservation buffer, and stored at -80\u0026deg;C by the Roy Alcalay Lab at Columbia University. Samples were delivered on dry ice and upon delivery samples were immediately stored at -80\u0026deg;C until use. Control Samples: female n\u0026thinsp;=\u0026thinsp;20, male n\u0026thinsp;=\u0026thinsp;16 (1 null); PD samples: female n\u0026thinsp;=\u0026thinsp;18 (1 null), male n\u0026thinsp;=\u0026thinsp;18 (sample demographics are outlined in Table\u0026nbsp;1). The study protocol for human blood collection and the consent form was reviewed and approved by the Institutional Review Boards of The Columbia University. Participants were provided with informed consent. The coded samples were shared between Columbia University and University of Georgia and the unblinding occurred after all samples were processed and when the data was analyzed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eThawing and Preparation of PBMCs\u003c/h2\u003e \u003cp\u003ePBMC processing was adapted from Barcelo et al., 2018 \u003csup\u003e21\u003c/sup\u003e. Cryopreserved samples were submerged halfway for 60 seconds in a 37\u0026deg;C water bath. Immediately prior to full sample thaw 1 mL of pre-warmed (37\u0026deg;C) complete RPMI (RPMI, 10% FBS, 1% Pen/Strep) was added dropwise, pipetted against the tube wall. Thawed PBMCs were poured into a 15 mL conical tube containing 5 mL of pre-warmed (37\u0026deg;C) complete RMPI. Cryovials were rinsed with 2 mL of pre-warmed (37\u0026deg;C) complete RPMI and then poured into the previously used conical tube with cell mixture. PBMCs were incubated for 5 minutes in a 37\u0026deg;C water bath. PBMCs were then pelleted for 10 minutes at 1500 rpm, at room temperature. Supernatant was discarded and 1 mL of pre-warmed (37\u0026deg;C) complete RPMI with 50 U/mL of DNase (Roche, Cat# 04-716-728-001, 10 units/\u0026micro;L) was added, resuspension was done without pipetting. PBMCs were then incubated for 1 hour at 37\u0026deg;C in a water jacketed incubator (5% CO\u003csub\u003e2\u003c/sub\u003e, 95% humidity) with tube cap loosened. Following incubation PBMCs were pelleted and resuspended for counting in preparation for flow cytometry.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eAntibodies, Titration and Staining Protocol\u003c/h2\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003eAntibody Titration\u003c/h2\u003e \u003cp\u003eAll antibodies and Live/Dead stain: CD45-PacBlue (1:200, clone HI30, BioLegend), CD14-PerCP/Cy5.5 (1:100, HCD14, BioLegend), CD19-PerCP/Cy5.5 (1:100, HIB19, BioLegend), CD3-APC/Cy7 (1:50, HIT3a, BioLegend), CD56-APC (1:100, HCD56, BioLegend), CD16-PE/Cy7 (1:100, 3G8, BioLegend), NKG2D-FITC (1:100, 1D11, BioLegend), NKG2A-PE (1:100, 131411, R\u0026amp;D), CX3CR1-BV711 (1:100, 2A9-1, BioLegend), and Zombie Yellow (423103, BioLegend) were individually titrated using Veri-Cells (Cat# 425001, BioLegend) to determine optimal staining concentrations.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003eStaining\u003c/h2\u003e \u003cp\u003ePrepared PBMCs were transferred to a 96-well plate, pelleted (1,500rpm for 5 minutes at room temp) and washed with PBS. PBMCs were incubated with Zombie Yellow (1:500) for 20 minutes, at room temperature, in the dark. PBMCs were washed with FACS Buffer (0.1% BSA, 1 mM EDTA, 0.01% Sodium Azide, and PBS) and pelleted. Samples were then resuspended in FACS Buffer with Human TruStain FcX (1:20, Cat# 422302, BioLegend) for 10 minutes at room temperature. Samples were then pelleted and resuspended in antibody master mix at a ratio of 1x10\u003csup\u003e6\u003c/sup\u003e cells/100\u0026micro;L master mix. Cells were incubated for 20 minutes at room temperature in the dark. Cells pelleted and washed twice with PBS. Prior to analysis samples were pelleted and resuspended in 2% paraformaldehyde. Samples were analyzed immediately after preparation. Single-color controls were prepared for each run using UltraComp eBeads (Cat# 01-2222-42, Thermo Fisher Scientific).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eFlow Cytometry: Acquisition and Experimentation Standardization\u003c/h2\u003e \u003cp\u003eSamples were analyzed using a NovoCyte Quanteon Flow Cytometer (Agilent Technologies). The system used has 4 excitation lasers: 405 nm, 488 nm, 561 nm and 640 nm. Prior to sample analysis, instrumentation performance was evaluated by the quality control (QC) procedure, experiments were only run if performance was optimal. To establish study standardization longitudinally, antibody titration was performed, and optimal antibody concentrations were determined. Using optimal antibody concentrations, instrument gain settings were established for each parameter by evaluation of single-positive signals and confirmation that all positive events were below the maximum dynamic range of the instrument (7.2 log). Using established gains for all parameters, compensation was calculated, fluorescence minus one (FMO) controls, and single color controls were collected, to ensure downstream analysis accuracy of determined positive event populations. A minimum of 100,000 events were collected per sample to ensure robust breadth of population distributions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis and Quantitation\u003c/h2\u003e \u003cp\u003eAnalysis of flow cytometry data was carried out using FlowJo 10.8 (BD Biosciences). Statistical analysis was performed using Graphpad Prism (Graphpad Software, v9.3.1). A P-value of less than 0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eData Availability\u003c/h2\u003e \u003cp\u003eThe datasets generated during and/or analyzed during the current study are available from the corresponding author.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by MJFF Research Grant ID MJFF-019068 and NIH/NINDS R01NS119610-01.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no conflict of interest to report.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eS.W. performed the experiments on PBMCs, the data analysis and wrote the manuscript. K.B.M. performed the data analysis of PMBCs and wrote the manuscript. R.N.A. selected the patient cohort for the PBMC and provided data interpretation.\u0026nbsp; J.A.L, and C.C.L provided data interpretation. J.K.L conceived the experimental plan, supervised the work and wrote the manuscript. All the authors contributed to the manuscript preparation.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003ePajares, M., I. Rojo, A., Manda, G., Bosc\u0026aacute;, L. \u0026amp; Cuadrado, A. Inflammation in Parkinson\u0026rsquo;s Disease: Mechanisms and Therapeutic Implications. Cells \u003cb\u003e9\u003c/b\u003e, 1687 (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCen, L. \u003cem\u003eet al.\u003c/em\u003e Peripheral Lymphocyte Subsets as a Marker of Parkinson's Disease in a Chinese Population. 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Current Protocols in Cytometry \u003cb\u003e84\u003c/b\u003e, e35, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/cpcy.35\u003c/span\u003e\u003cspan address=\"10.1002/cpcy.35\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2018).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"npj-parkinsons-disease","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"npjparkd","sideBox":"Learn more about [npj Parkinson's Disease](http://www.nature.com/npjparkd/)","snPcode":"41531","submissionUrl":"https://submission.springernature.com/new-submission/41531/3","title":"npj Parkinson's Disease","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Natural killer (NK) cells, NKG2D, NKG2A, CX3CR1, Parkinson’s Disease, UPDRS","lastPublishedDoi":"10.21203/rs.3.rs-1883506/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1883506/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMounting data suggest an important role of the immune system in Parkinson\u0026rsquo;s disease (PD). Previous evidence of increased natural killer (NK) cell populations in PD suggests a potential role of NK cells in the pathogenesis of the disease. Previous studies have analyzed NK populations using aggregation by a variable expression of CD56 and CD16. It remains unknown what differences may exist between NK cell subpopulations when stratified using more nuanced classification. Here we profile NK cell subpopulations and elucidate the expressions of activating NKG2D receptor, inhibitory NKG2A receptor, and homing CX3CR1 receptor on NK cell subpopulations in PD and healthy controls (HC). The cryopreserved PBMC samples were analyzed using a 10-color flow cytometry panel to assess NK cell subpopulations on 36 individuals with sporadic PD and 35 HC participants. Among PD cases, we observed that NKG2D frequency and expression level was higher in CD56\u003csup\u003ebright\u003c/sup\u003e NK populations in patients with more severe motor symptoms as measured by the UPDRS III. Additionally, NKG2D expression intensity in CD56\u003csup\u003ebright\u003c/sup\u003e NK populations was associated with disease duration. NK subpopulations revealed a significant difference in CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003e+/\u0026minus;\u003c/sup\u003e NK cell subpopulations, with all PD groups showing significantly greater expression of NKG2D on CD56\u003csup\u003ebright\u003c/sup\u003eCD16\u003csup\u003ebright\u003c/sup\u003e NK cells compared to HC. Overall, we identified changes in NK profiles in PD that change with disease duration and motor symptom severity. Future studies should assess whether these changes in NK populations account for disease progression.\u003c/p\u003e","manuscriptTitle":"Distinctive blood CD56bright NK cell subset profile and increased NKG2D expression in CD56bright NK cells in Parkinson’s disease","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-08-09 17:59:12","doi":"10.21203/rs.3.rs-1883506/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2022-09-26T07:03:30+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2022-09-16T15:17:47+00:00","index":2,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2022-09-01T16:07:39+00:00","index":3,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2022-08-24T14:04:29+00:00","index":3,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2022-08-24T11:23:11+00:00","index":2,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2022-08-22T00:06:34+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2022-08-08T08:01:05+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2022-08-07T19:09:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2022-07-26T06:15:07+00:00","index":"","fulltext":""},{"type":"checksFailed","content":"","date":"2022-07-22T07:22:51+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2022-07-22T00:38:18+00:00","index":"","fulltext":""},{"type":"submitted","content":"npj Parkinson's Disease","date":"2022-07-22T00:38:17+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"npj-parkinsons-disease","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"npjparkd","sideBox":"Learn more about [npj Parkinson's Disease](http://www.nature.com/npjparkd/)","snPcode":"41531","submissionUrl":"https://submission.springernature.com/new-submission/41531/3","title":"npj Parkinson's Disease","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"02223dd9-ff9e-450b-b3ec-05a96d57a0cd","owner":[],"postedDate":"August 9th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-02-16T08:11:55+00:00","versionOfRecord":{"articleIdentity":"rs-1883506","link":"https://doi.org/10.1038/s41531-024-00652-y","journal":{"identity":"npj-parkinsons-disease","isVorOnly":false,"title":"npj Parkinson's Disease"},"publishedOn":"2024-02-15 05:00:00","publishedOnDateReadable":"February 15th, 2024"},"versionCreatedAt":"2022-08-09 17:59:12","video":"","vorDoi":"10.1038/s41531-024-00652-y","vorDoiUrl":"https://doi.org/10.1038/s41531-024-00652-y","workflowStages":[]},"version":"v1","identity":"rs-1883506","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1883506","identity":"rs-1883506","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}