Original Article
Narcolepsy type 1 patients have lower levels of effector memory CD4 þ T cells compared to their siblings when controlling for
H1N1-(Pandemrix ™ )-vaccination and HLA DQB1 * 06:02 status
Rannveig Viste
a,b, Benedicte A. Lie
c,d, Marte K. Viken
c,d, Terje Rootwelt
b,e, Stine Knudsen-Heier
a,1, Birgitte R. Kornum
f,*,1aNorwegian Centre of Expertise for Neurodevelopmental Disorders and Hypersomnias (NevSom), Department of Rare Disorders, Oslo University Hospital, Norway
bInstitute of Clinical Medicine, University of Oslo, Norway
cDepartment of Immunology, University of Oslo and Oslo University Hospital, Norway
dDepartment of Medical Genetics, University of Oslo and Oslo University Hospital, Norway
eDivision of Paediatric and Adolescent Medicine, Oslo University Hospital, Norway
fKornum Laboratory, Department of Neuroscience, University of Copenhagen, Denmark
a r t i c l e i n f o
Article history:
Received 22 February 2021 Received in revised form 15 June 2021
Accepted 13 July 2021 Available online 22 July 2021 Keywords:
Narcolepsy type 1 T cell differentiation CD25 activation markers CD69 activation markers Post influenza A (H1N1) pandemic H1N1 (Pandemrix™) vaccination
a b s t r a c t
Study objectives: Evidence suggests a cell-mediated autoimmune pathogenesis for narcolepsy type 1 (NT1), but it is not clear whether the disease is associated with overall changes in T cell subsets. The increase in NT1 incidence after H1N1 vaccination campaign with the Pandemrix™vaccine suggests that disease-relevant changes in the immune system following this vaccination were important. In this study, we aimed to investigate differentiated T cell subsets and levels of CD25 and CD69 activation markers in a cohort of mainly Pandemrix™-vaccinated NT1 patients compared with their vaccinated and unvacci- nated siblings.
Methods:Peripheral blood mononuclear cells were collected in parallel and analysed with flow cytometry in 31 NT1 patients with disease onset after the 2009 influenza A (H1N1) pandemic and/or Pandemrix™ vaccination and 45 of their non-narcoleptic siblings (29/31 and 34/45 vaccinated, respectively).
Results:We observed significantly lower effector memory CD4þT cell levels in NT1 patients compared to their siblings, when controlling for HLA DQB1*06:02 and vaccination status. Further, within the sibling group, vaccination status significantly affected frequencies of central memory and CD8þCD25þT cells, and HLA DQB1*06:02 status significantly affected frequencies of CD4þCD25þT cells.
Conclusion: We confirm that NT1 is associated with lower levels of effector memory CD4þT cells in peripheral blood. Importantly, thisfinding was only significant when controlling for vaccination and HLA status in both patients and controls. We thus demonstrate the importance of characterizing such factors (eg HLA and vaccination) when studying T cell subsets in NT1. This might explain earlier conflicting results.
©2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
1. Introduction
Narcolepsy type 1 (NT1) is a relatively rare, chronic sleep dis- order of central nervous origin, characterized by instability of sleep/
wake regulation, symptoms such as excessive daytime sleepiness with sleep attacks and fragmented nocturnal sleep with awaken- ings, and by instability of rapid eye movement (REM) sleep regu- lation resulting in REM sleep dissociation phenomena like cataplexy (brief loss of muscle tone triggered by emotions), sleep Abbreviations:AHI, apnoea/hypopnoea index; CSF hcrt-1, cerebrospinalfluid
hypocretin-1; CV, coefficient of variance; ESS, Epworth sleepiness scale score; FMO, fluorescence minus one; ICSD-3, International Classification of Sleep Disorders, third edition (ICSD-3); mAbs, monoclonoal antibodies; MSLT-sl, multiple sleep la- tency test sleep latency; NT1, narcolepsy type 1; PBMC, peripheral blood mono- nuclear cells; PSG, polysomnography; REM, rapid eye movement; SOREMP, sleep onset REM period; TEMRA, terminally differentiated effector memory T cells.
*Corresponding author. Department of Neuroscience, University of Copenhagen, Panum 24-6-14, Norre Alle 14, 2200, Copenhagen N, Denmark.
E-mail address:[email protected](B.R. Kornum).
1SKH and BRK contributed equally to this study.
Contents lists available atScienceDirect
Sleep Medicine
j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / s l e e p
https://doi.org/10.1016/j.sleep.2021.07.024
1389-9457/©2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
paralysis, hypnagogic hallucinations, and REM sleep behaviour disorder [1,2].
NT1 symptoms are most likely caused by cell-mediated auto- immune destruction of the neurons in the hypothalamus that produce the neuropeptides hypocretin-1 and 2 (also known as orexin-A and -B) [3,4]. This is supported by genetic findings, including a strong association with the HLA class II allele DQB1*06:02, which is present in 86e98% of patients compared with 15e33% of the general population [5e10]. Genetic variants in other HLA and non-HLA genes involved in immune system re- sponses are also confirmed as being NT1 risk factors [10e12]. In the search for specific autoimmune involvement, a few studies have identified autoantibodies in patients with NT1, but none has been shown to be specific to narcolepsy [13e15]. Likewise, in a search for autoreactive T lymphocytes, one study detected autoreactive CD8þ T cells that recognize peptides from hypocretin producing neurons not only in patients, but also in controls [16]. Three independent studies have identified CD4þT cells that are autoreactive towards hypocretin peptides in NT1 patients, strengthening the autoim- mune hypothesis [17e19].
Further evidence for an immune disease mechanism comes from the associations with environmental factors, such as upper airway infections, data from which show increased titres of strep- tococcal antibodies in recent-onset NT1 [14], a seasonal variation in narcolepsy incidence [20], and a 3-fold increase in NT1 incidence after the 2009 influenza A (H1N1) pandemic in Beijing [20,21].
Notably, immunisation with the Pandemrix™vaccine against the 2009 influenza A (H1N1) was followed by a 3-17-fold increase in new NT1 cases for several years after vaccination [22e27]. Despite considerable research, the indications of an autoimmune disease mechanism in NT1 are strong but not proven, and the precise dis- ease mechanism for immune involvement in NT1 and the effect of the Pandemrix™vaccine in patients who developed NT1, remain to be elucidated [28].
In an attempt to characterize disease-relevant changes in the immune system in NT1, three studies have already investigated whether NT1 patients have a specific immune signature that in- cludes specific T cell subsets [29e31]. Overall, the three studies found no differences in frequencies of CD4þ and CD8þ T cells compared with controls [29e31]. They further gave somewhat conflicting results about the distributions of differentiated memory and naïve T cell subsets as well as levels of the CD69 and CD25 activation markers. We speculate that this could be due to differ- ences in study cohort size and design (eg number of patients, age, disease duration, vaccination status, HLA DQB1*06:02 status, different sample collection time for patients vs. controls). Hart- mann et al. (2016) investigated immune cell subsets in a mixed group of 11 Pandemrix™-vaccinated and 28 unvaccinated NT1 patients and 25 HLA DQB1*06:02-positive controls of unknown vaccination status [29]. Lecendreux et al. (2017) compared 13 Pandemrix™-vaccinated and 15 unvaccinated NT1 patients with 32 controls of unknown vaccination and HLA status [30]. Moresco et al.
(2018) included 14 adult NT1 patients and 13 HLA DQB1*06:02- negative controls (the vaccination status of patients and controls was not known) [31].
In this study, we aimed to understand whether a general T cell signature is present in NT1 patients compared with their non- narcoleptic siblings, and importantly determine whether HLA DQB1*06:02 and/or Pandemrix™ vaccination status affected the results. We investigated this in a well-characterized cohort of NT1 patients and their siblings. Importantly, blood sampling and bio- bank processing of patients and siblings were conducted in parallel in an identical manner. Peripheral blood mononuclear cells (PBMCs) were assessed byflow cytometry. We quantified the CD4þ and CD8þ T cell frequencies, the differentiated T cell subsets
(distinguished by CD45RA and CCR7 staining) and the levels of the two activation markers CD25 and CD69 on CD4þand CD8þT cells.
2. Method 2.1. Study subjects
In the period between February 2015 and November 2018, 107 Norwegian NT1 patients and their first-degree relatives partici- pated in family counselling and education courses at our national centre (Norwegian Centre of Expertise for Neurodevelopmental Disorders and Hypersomnias (NevSom)). The NT1 diagnosis was verified in patients and evaluated in relatives according to the In- ternational Classification of Sleep Disorders, third edition (ICSD-3) [1], by an experienced narcolepsy expert (SKH). The cohort was selected to be as homogeneous as possible. Hence, only families where patient's disease onset was between October 2009 (ie, onset after the 2009 influenza A H1N1 pandemic and/or Pandemrix™ vaccination) and December 2013 were selected (Table 1). To avoid inclusion bias, the patients were included consecutively regardless of H1N1 vaccination status. In this way, two unvaccinated patients were included. In general, due to recall bias, it is not known whether the unvaccinated patient or relatives have been exposed to the influenza A (H1N1) virus during the 2009/10 influenza A (H1N1) pandemic or the following years (the influenza A H1N1 virus reoccurred as a seasonal influenza the following years).
Furthermore, there are no reliable data on H1N1 infection rates in the Norwegian population as the recommendations from the health authorities during the H1N1-pandemic was that those that felt ill from influenza should stay at home.
The study protocol was approved by the Regional Ethics Com- mittee (REC South-East 2014#450/2014#451). Written informed consent was obtained from all participants prior to inclusion. Par- ents signed on behalf of their children. Data from some of the present study cohort have been presented in previous publications [10,32e39].
All participants (patients and siblings) underwent 1e2 weeks of actigraphy followed by overnight polysomnography and a multiple sleep latency test (MSLT) withfive nap opportunities (30 min) at 2- h intervals on the following day. All were physically examined, had blood samples drawn and received semi-structured interviews about narcolepsy symptoms (Stanford sleep questionnaire and REM sleep behaviour disorder questionnaire [40,41]), comorbidities, and medication use. Self-reported severe daytime sleepiness was defined as an Epworth sleepiness scale (ESS) score11/24 [42].
HLA typing and cerebrospinal fluid hypocretin-1 (CSF hcrt-1) measurements in patients were performed as previously described [39,43]. Pandemrix™vaccination status was confirmed from the Norwegian Immunisation Registry (SYSVAK).
All patients paused intake of drugs influencing sleep or cata- plexy two weeks before their sleep recordings were made. None of the siblings included were taking any medications that affected their sleep. Exclusion criteria were: presence of acute infection, use of systemic anti-inflammatory or immunosuppressive medication, and serious medical or psychiatric disorders that made it difficult to complete the study. One patient who used a local asthma medi- cation (a combined salmeterol/fluticasone inhaler) was included, whereas two siblings who were treated with steroid injections to treat allergy and with mesalasin tablets to treat ulcerous colitis, respectively, were excluded. Three patients with mild, untreated psoriasis were included.
The process of cohort selection is presented in theflow chart in Fig. 1. Briefly,flow cytometry analyses of 49 patients and 64 non- narcoleptic siblings were planned. However, after thawing, sam- ples from 11 patients and 14 siblings had too few cells to carry out
the analyses and had to be excluded from the study. Further, 12 samples (from 7 patients and 5 siblings) failed to pass the flow cytometry quality control and were excluded, leaving samples from 31 patients and 45 siblings.
2.2. Analyses of T cell subsets
Fasting blood samples were drawn between 7 and 9 AM for routine blood parameter screening, HLA-typing, and lymphocyte Table 1
Demography and clinical variables of NT1 patients and their siblings.
NT1 patients (N¼31)
Siblings (N¼45)
p
Sex (female/male) 22/9 24/21 NS
Age at inclusion, year (median (minemax)) 18 (8.3e62) 18 (7.8e52) NS
H1N1 (Pandemrix™) vaccination, yes (% (n/N)) 94 (29/31) 76 (34/45) NS
HLA DQB1a06:02, yes (% (n/N)) 100 (31/31) 64 (29/45) NS
CSF hcrt-1110 pg/ml, yes (% (n/N)) 100 (27/27)a
Age at NT1 onset, year (median (minemax)) 13 (6.3, 54)
NT1 duration, year (median (minemax))b 6.3 (1.8e7.9)
Days from vaccination to onset NT1 (median (minemax)) 139 (2e1382)
Cat, yes (% (n/N)) 100 (31/31) 4.4 (2/45)c <0.001
HH, yes (% (n/N)) 87 (27/31) 25 (11/44)d 0.003
SP, yes (% (n/N)) 71 (22/31) 16 (7/44)d 0.002
ESS score, median (minemax) 19 (11e24) 4.0 (0e16) <0.001
SOREMPs MSLT, yes (% (n/N))e 100 (27/27) 15 (6/40)f <0.001
MSLT-sl, minutes (median (minemax))e 1.0 (0.3e13)
(N¼27)
16 (5.2e20) (N¼40)
<0.001 CSF hcrt-1¼cerebrospinalfluid hypocretin-1 levels; NT1¼narcolepsy type 1; Cat¼cataplexy; HH¼hypnagogic hallucinations; SP¼sleep paralysis; ESS score¼Epworth Sleepiness Scale score (possible range is 0e24); SOREMP¼sleep-onset rapid eye movement sleep period; MSLT-sl¼multiple sleep latency test mean sleep latency; NS¼not statistically significant.
aFour patients had no CSF hcrt-1 measure, but had clear-cut cataplexy and a positive MSLT test and were included.
bDisease duration was calculated as age at inclusion minus age at disease onset.
c Cataplexy-like symptoms (rare episodes of muscle weakness in hands when laughing).
dData on HH and SP is missing in one sibling.
eMSLT results are only presented for the 27 NT1 patients and 40 siblings with valid overnight polysomnography (ie, total minimum sleep time of 6 h and AHI5 events/
hour).
fFour siblings had one SOREMP on MSLT recordings, and two siblings had two SOREMPs (but MSLT-sl>8 min).
Fig. 1.Theflow chart depicts the NT1 patients and their non-narcoleptic siblings analysed byflow cytometry. The 49 patients planned for cell analyses had between one and four siblings included in the project simultaneously. Those siblings sum up to the 64 siblings that were selected for cell analyses. NT1¼narcolepsy type 1; ICSD-3¼International Classification of Sleep Disorders, third edition; CSF hcrt-1¼cerebrospinalfluid hypocretin-1.
analyses. For the purpose of the latter, PBMCs were separated from full blood following density-gradient centrifugation, then washed and stored in liquid nitrogen until use. Thawed cells were washed and stained with commercially manufactured monoclonal anti- bodies (mAbs: CD3:BV421, CD45RA:PerCP-Cy5.5, CCR7:APC, CD25:PE-CY7, CD4:FITC and CD69:PE) and isotype controls in optimal concentrations. Information about the mAbs used is sum- marised inTable S1. The protocol for staining cells is described in the Supplementary Material.
Flow cytometry analyses were done using three laser LSR- Fortessa cell analyzers running BD FACSDiva v 8.0.1 software (BD Biosciences, Becton, Dickinson and Company). FlowJo v10 software (FlowJo LLC, Ashland, Oregon, USA) was used for post-analyses.
Prior to all analyses, controls (unstained cells, live/dead and“fluo- rescence minus one” [FMO]) were run. 100,000 events were collected per sample. The coefficient of variation (CV) in duplicate samples varied from 0 to 46%. Samples with a CV > 20% were excluded from analyses. One of the samples included had no duplicate.
Cells were gated visually, guided by FMO controls. The gating strategy for CD4þ T cells is shown inFig. S1. An identical gating strategy was adapted for CD4-T cells (hereafter denoted CD8þT cells). Briefly, CD3 and CD4 markers defined the CD4þ(CD4þCD3þ) and CD8þ(CD4-CD3þ) T cell subsets. CD4þand CD8þT cell subsets were further segregated into the differentiated T cell subsets: naïve T cells (CD45RAþCCR7þ), central memory T cells (CD45RACCR7þ), effector memory T cells (CD45RA CCR7-) and terminally differ- entiated effector memory T (TEMRA) cells (CD45RAþ CCR7-) (Fig. S1c). Finally, cells positive for the CD25 activation marker were gated directly in CD4þand CD8þT cells (Fig. S1e), and the CD69 marker was gated in CD4þand naïve CD8þT cells (Fig. S1d), and directly in CD4þand CD8þT cell subsets (Fig. S1f).
2.3. Statistics
All data exported from FlowJo were analysed in R/RStudio (http://r-project.org). Patients and siblings could not be perfectly age matched, but there was no significant difference in age distri- butions between NT1 patients and their siblings. In the analyses, we applied the linear mixed-effect model from the lme4 package for R, which takes into account the family relatedness of the cohort [44]. The linear mixed-effect model calculates both fixed effect estimates (parameters that do not vary across individuals) and random effect estimates (such as the within-participant variation caused by family relatedness in the cohort). When necessary, the T cell subsets were log2 or square root transformed to meet model assumptions. In the models applied inTables 2 and 3, outcomes were the different T cell subsets. The covariates included in both models were age at inclusion (continuous), HLA DQB1*06:02 (dichotomous:þ/), HIN1 vaccination (dichotomous:þ/) and the term calculating the mixed-effect caused by the family relatedness in the cohort. InTable 2, NT1 patients were compared with their siblings, hence, disease status (dichotomous: patient/sibling) was additionally included as covariate in that model. The frequencies presented inTable 1were compared using Fisher's exact test. Allp values and 95% confidence intervals were two-sided.
3. Results
3.1. Demographics, clinical variables and sleep parameters
Demographics, clinical variables, and sleep parameters from sleep recordings for all patients and siblings with valid cell analyses (NT1¼31; siblings¼45) are summarised inTable 1. Note that the MSLT sleep latency (MSLT-sl) and number of MSLT sleep onset REM
periods (SOREMPs) are only calculated for participants with a total sleep time6 h and apnoea/hypopnoea index (AHI)5 events/
hour (NT1¼27; siblings¼40).
The patients investigated were typical NT1 patients with severe daytime sleepiness, clear-cut cataplexy, HLA DQB1*06:02- positivity, low CSF hypocretin-1 and/or a positive MSLT (MSLT- sl8 min;2 SOREMPS). Ninety-four percent were Pandemrix™- vaccinated. None of the recruited siblings fulfilled the ICSD-3 criteria for NT1 (ie, non-narcoleptic). Consequently, the siblings were generally not excessively sleepy (median [minemax] ESS score ¼ 4.0 [0e16]) and had a normal MSLT-sl (median [minemax]¼16 [5.2e20] minutes). Three siblings had higher ESS scores (11/24, 13/24 and 16/24, respectively) but no objective sleepiness (ie, mean MSLT-sl>8 min), and a fourth sibling had an ESS score of 16/24, MSLT-sl of 8.0 min but no SOREMPs, no cata- plexy, and denied feeling excessive sleepy or having trouble staying awake in everyday life. Three other siblings had an MLST-sl8 min but no subjective sleepiness (ie, their ESS score were10/24) and no SOREMPs; six siblings had 1 or 2 MSLT SOREMPs but with a mean MSLT-sl above 8 min. Vaccination coverage in the sibling group was 76%, and 64% were HLA DQB1*06:02-positive.
3.2. Lower levels of effector memory CD4þT cells in NT1 patients compared with their siblings when controlling for HLA and vaccination status
To minimize the effects of genetic and environmental variables, NT1 patients were compared by the linear mixed-effect model with their non-narcoleptic siblings, from whom blood samples were drawn at the same time (7e9 AM) and, in most cases, on the same day, and then processed for parallel biobanking. The results (Table 2 andFig. 2C) demonstrate that the NT1 patients had significantly lower levels of effector memory CD4þT cells compared with their siblings (b¼ 0.42, 95% CI¼ 0.81 to0.024,p¼0.043). This finding was only significant when the model included HLA, vacci- nation status and age as covariates, and not when only adjusting for age (Table S2). For the other included T cell subtypes, we did not find statistically significant disease specific differences (Table 2).
We did observe a trend towards higher levels of naïve CD4þT cells in NT1 patients (Fig. 2A andTable 2), and we also noticed a sub- group of patients with high levels of CD8þCD25þT cells (Fig. 3B).
This subgroup could not be distinguished from the rest of the NT1 patients based on any other disease/demographic parameter included in our analysis (such as age, disease duration, CSF hcrt-1 level). Besides these disease specificfindings, we found that age had a statistically significant effect on the distribution of CD4þand CD8þT cells in the CD3þcompartment (CD4:b¼0.30, 95% CI¼0.12 to 0.48, p ¼0.002; CD8: b¼ 0.30, 95% CI ¼ 0.48 to0.12, p¼0.002), and further the fraction of effector memory CD4þcells increased with age (b¼0.032, 95% CI¼0.008 to 0.056,p¼0.012) (Table 2). Age effects were expected, as it is well known that the composition of T cell subtypes changes with age [45,46]. In the entire cohort, H1N1-vaccinated individuals (patients and siblings) had significantly higher levels of effector memory CD4þ T cells (b¼0.60, 95% CI¼0.064 to 1.1,p¼0.032) and CD4þTEMRAcells (b¼1.3, 95% CI¼0.11 to 2.5,p¼0.037) compared with unvacci- nated individuals (Table 2).
3.3. Higher levels of central memory CD8þT cells and lower levels of CD8þCD25þT cells in vaccinated siblings compared with
unvaccinated siblings
The increase in the frequency of new NT1 cases after the H1N1 (Pandemrix™) vaccination campaign indicates that this vaccine may be associated with disease-relevant modifications of the
Table 2
A comparison of T cell subsets, differentiated T cell subsets and levels of CD25 and CD69 markers in patients and siblings with adjustment for age, HLA DQB1*06:02 status, and H1N1 vaccination status.
NT1 patients (n¼31)
Siblings (n¼45)
Linear mixed- effect model p
Previousfindings (patients compared with controls)a
Current paper A B C
CD3þT cells, % of live lymphocytes 73 (63, 83) 73 (63, 81) 0.307 4 4 4 4
CD4þT cells, % of CD3þT cells 69 (65, 72) 66 (62, 71) 0.635¤ 4 4 4 4
CD8þT cells, % of CD3þT cells 31 (28, 35) 34 (29, 38) 0.635¤ 4 4 4 4
Naïve, % of CD4þT cells 23 (19, 31) 19 (13, 30) 0.084 4([) [ 4(Y) 4
Central memory, % of CD4þT cells 66 (59, 74) 68 (58, 72) 0.522 4 4([) [ 4
Effector memory, % of CD4þT cells 5.8 (4.2, 11) 10 (5.8, 15) 0.043*,¤,# Y Y 4 4(Y)
EMRA, % of CD4þT cells 0.17 (0.066, 0.51) 0.25 (0.087, 1.0) 0.570# 4 4 NA Y
CD25þ, % of CD4þT cells 7.4 (6.1, 9.5) 8.0 (5.7, 12) 0.612 4 NA [ NA
CD69þ, % of CD4þT cells 1.1 (0.64, 3.1) 1.4 (0.71, 3.1) 0.794 4 NA [ NA
CD69þ, % of Naive CD4þT cells 2.9 (1.2, 4.4) 2.9 (1.1, 3.8) 0.348 4 [ NA NA
Naïve, % of CD8þT cells 28 (23, 37) 28 (20, 35) 0.127 4 [ 4 4
Central memory, % of CD8þT cells 39 (27, 47) 37 (25, 45) 0.569 4 4 4 4([)
Effector memory, % of CD8þT cells 18 (13, 28) 22 (18, 30) 0.327 4 Y 4 4
EMRA, % of CD8þT cells 8.9 (4.1, 17) 9.2 (5.8, 14) 0.622 4 4 4 4(Y)
CD25þ, % of CD8þT cells 3.3 (2.1, 4.8) 2.3 (1.9, 4.5) 0.149 4 NA 4 NA
CD69þ, % of CD8þT cells 3.9 (2.8, 5.6) 3.9 (2.6, 5.7) 0.924 4 NA [ NA
CD69þ, % of Naive CD8þT cells 3.3 (1.9, 4.7) 2.8 (1.7, 3.8) 0.584 4 4 NA NA
All values are listed as median (interquartile range); EMRA¼terminally differentiated effector memory; a linear mixed-effect model was used. The outcome variables are T cell subsets; the predictors are disease status (dichotomous: patient/sibling), HLA DQB1*06:02 status (dichotomous:þ/), vaccination status (dichotomousþ/), age at inclusion (continuous), and the term calculating the mixed effect caused by the family relatedness in the cohort.
Bold and*pis significant at 0.05 levels, not corrected for multiple comparisons. Patients had significantly lower effector memory CD4þT cells than siblings (b¼ 0.42, 95%
CI¼ 0.81 to0.024,p¼0.043);¤Age was statistically significant in CD4þand CD8þcompartments (CD4:b¼0.30, 95% CI¼0.12 to 0.48,p¼0.002; CD8:b¼ 0.30, 95%
CI¼ 0.48 to0.12,p¼0.002) and in effector memory CD4þT cells (b¼0.032, 95% CI¼0.008 to 0.056,p¼0.012);#vaccinated individuals (patients and siblings), had significantly higher levels of effector memory CD4þT cells (0.60, 95% CI¼0.064 to 1.1,p¼0.032) and CD4þTEMRAcells (b¼1.3, 95% CI¼0.11 to 2.5,p¼0.037) compared with unvaccinated individuals.
aA¼Hartmann et al. (2016); B¼Lecendreux et al. (2017); C¼Moresco et al. (2018);4¼no differences between patients and controls;[¼levels in patients significantly higher in patients compared with controls;Y¼levels in patients significantly lower in patients compared with controls; NA¼not measured; (Y) or ([)¼non-significant tendencies in the data.
Table 3
Comparisons of T cell subsets, differentiated T cell subsets and levels of CD25 and CD69 markers in siblings and effects of age, HLA DQB1*06:02 status, and H1N1 vaccination status.
Age DQB1*06:02
(ref¼HLA-)
H1N1 vaccination (ref¼vac-)
Previousfindings (effect of vaccination)a
В p b p b P Current paper A B
CD3þT cells, % of live lymphocytes 0.016 0.955 2.5 0.583 2.1 0.681 4 4 [
CD4þT cells, % of CD3þT cells 0.33 0.011* 3.6 0.094 2.0 0.393 4 4 4
CD8þT cells, % of CD3þT cells ¡0.33 0.011* 3.6 0.094 2.0 0.393 4 4 [
Naïve, % of CD4þT cells 0.16 0.450 3.5 0.282 3.3 0.357 4 4 4([)
Central memory, % of CD4þT cells 0.067 0.623 0.13 0.940 3.6 0.058 4(Y) 4 4(Y)
Effector memory, % of CD4þT cells 9.0103 0.587 0.22 0.452 0.36 0.282 4 4 4
EMRA, % of CD4þT cells 0.033 0.387 0.13 0.845 0.60 0.429 4 4 NA
CD25þ, % of CD4þT cells 3.4103 0.789 ¡0.46 0.016* 0.067 0.707 4 NA 4
CD69þ, % of CD4þT cells 0.016 0.573 0.60 0.229 0.37 0.512 4 NA 4
CD69þ, % of Naive CD4þT cells 0.013 0.233 0.33 0.071 0.096 0.628 4 4 NA
Naïve, % of CD8þT cells 0.15 0.432 2.5 0.366 2.1 0.486 4 4 4
Central memory, % of CD8þT cells 0.10 0.624 3.5 0.339 9.2 0.031* [ 4 4
Effector memory, % of CD8þT cells 4.1104 0.973 0.077 0.730 0.24 0.359 4 4 4
EMRA, % of CD8þT cells 5.6103 0.735 0.32 0.258 0.46 0.156 4 4 4
CD25þ, % of CD8þT cells 7.5103 0.262 0.056 0.510 ¡0.21 0.031* Y NA Y
CD69þ, % of CD8þT cells 1.3103 0.923 0.075 0.729 7.0103 0.976 4 NA 4
CD69þ, % of Naive CD8þT cells 9.7103 0.639 0.42 0.243 0.15 0.714 4 4 NA
EMRA¼terminally differentiated effector memory cells.
Age was significant in CD4þand CD8þcompartments (CD4:b¼0.33, 95% CI¼0.087 to 0.58,p¼0.011; CD8b¼ 0.33, 95% CI¼ 0.58 to0.087,p¼0.011). HLA DQB1*06:02- positive individuals had lower levels of CD25 activated CD4þT cells (b¼ 0.46, 95% CI¼ 0.78 to0.13,p¼0.016). Vaccinated individuals had higher expression of central memory CD8þT cells (b¼9.2, 95% CI¼1.2 to 17,p¼0.031) and lower levels of CD25 activated CD8þT cells (b¼ 0.21, 95% CI¼ 0.38 to0.046,p¼0.031).
Bold and*psignificant at 0.05 level, not corrected for multiple comparisons; a linear mixed-effect model was used. The outcome variables are T cell subset, predictors: age at inclusion (continuous), HLA DQB1*06:02 status (dichotomous:þ/), vaccination status (dichotomousþ/), and the term calculating the mixed effect caused by the family relatedness in the cohort.
aCurrent paper refers to differences found between vaccinated and unvaccinated siblings (this table). Previousfindings refer to differences found between vaccinated and unvaccinated NT1 patients: A¼Hartmann et al. (2016); B¼Lecendreux et al. (2017); the Moresco et al. (2018) paper did not look at vaccination; none of these three papers looked at the effect of HLA DQB1*06:02;4¼no differences between patients and controls;[¼levels in patients significantly higher in patients compared with controls;
Y¼levels in patients significantly lower in patients compared with controls; NA¼not measured; (Y) or ([)¼non-significant tendencies in the data.
immune system. However, it is still not known whether Pan- demrix™vaccinationper sealso affects the general T cell signature in non-narcoleptic individuals, and thereby whether different vaccination frequencies in the control groups could explain the discrepancy with the results of the studies [29e31] reported in Table 2. We therefore investigated whether the differentiated T cell subsets and activation marker levels differed between vaccinated and unvaccinated siblings. We found that the H1N1-vaccinated siblings had higher levels of central memory CD8þ T cells (b¼9.2, 95% CI¼1.2 to 17, p¼0.031), and lower levels of the
CD8þCD25þT cells (b¼ 0.21, 95% CI¼ 0.38 to0.046,p¼0.031) (Table 3 and Fig. 3A and B, respectively). Moreover, HLA DQB1*06:02 positive siblings had lower levels of CD4þCD25þT cells (b¼ 0.46, 95% CI¼ 0.78 to0.13,p¼0.016) and again, age had a significant effect on the distribution of CD4þand CD8þT cells in the CD3þ compartment (CD4: b ¼ 0.33, 95% CI ¼ 0.087 to 0.58, p¼0.011; CD8:b¼ 0.33, 95% CI¼ 0.58 to0.087,p¼0.011) (Table 3). A comparison of siblings with or without symptoms did not yield any significant differences in any of the T cell subsets or activation marker levels (Table S3).
Fig. 2. NT1 patients have a lower fraction of effector memory CD4þT cells compared to their siblings. Distribution of the differentiated CD4þT cells in NT1 patients (red) and siblings (blue). A) naïve CD4þT cells. B) central memory CD4þT cells. C) effector memory CD4þT cells. D) terminally differentiated effector memory (EMRA) CD4þT cells.*Patients had significantly lower levels of effector memory CD4þT cells compared with their non-narcoleptic siblings (p¼0.043; details inTable 2).
Fig. 3.CD8þT cell subsets in patients (red) and siblings (blue), including HLA DQB1*06:02 status and H1N1 vaccination. Fractions of A) central memory CD8þT cells and B) CD8þCD25þT cells out of total number of CD8þT cells in all patients and siblings; HLA-positive and vaccinated patients versus HLA-positive and vaccinated siblings; HLA-positive versus HLA-negative siblings; and vaccinated versus unvaccinated siblings, respectively.*Vaccinated siblings had significantly higher levels of central memory CD8þT cells and lower levels of activated CD8þCD25þT cells compared with unvaccinated siblings (p¼0.031 in both subsets; details inTable 3).
4. Discussion
We here usedflow cytometry to investigate potential changes in T cell composition in a cohort of mainly H1N1 (Pandemrix™) vaccinated patients with NT1 and their non-narcoleptic siblings of mixed HLA DQB1*06:02 and vaccination status.
We found similar overall CD4þand CD8þT cell frequencies in NT1 patients when compared with their siblings, which is concordant with those of previous studies comparing overall T cell distributions in mixed cohorts of Pandemrix™-vaccinated and unvaccinated NT1 patients [29,30], and in NT1 cohorts in which the vaccination status was not known [31].
However, when the T cells were segregated into differentiated subsets (naïve-, central memory-, effector memory- and terminally differentiated effector memory [EMRA] T cells), NT1 patients had significantly lower frequency of central memory CD4þ cells compared with their siblings. Importantly, thisfinding was only significant when we additionally controlled for HLA DQB1*06:02 and vaccination status in the total cohort (patients and siblings).
Since the four differentiated subsets always add up to 100%, a decrease in one subset will be followed by increases in other.
Accordingly, we observed a non-significant increase in naïve CD4þ T cells (p¼0.084) in patients compared to siblings. A similar shift in CD4þT cell composition in NT1 has been reported before. Hart- mann et al. (2016) investigated immune cell subsets approximately 5 years after disease onset in a mixed group of 11 Pandemrix™- vaccinated and 28 unvaccinated NT1 patients and 25 HLA DQB1*06:02-positive controls of unknown vaccination status. The study found that patients with NT1 had higher frequencies of naïve CD4þT cells and lower frequencies of effector memory CD4þT cells exactly like our study. Moresco et al. (2018) explored T cell differ- entiation in 14 adult HLA DQB1*06:02-positive NT1 patients and 13 HLA DQB1*06:02-negative controls (the vaccination status of pa- tients and controls was not known). They observed a lower fre- quency of CD4þ TEMRAcells in patients than in controls and - in concordance with Hartmann et al. (2016) and our study - a ten- dency towards a lower frequency of effector memory CD4þT cells [31]. The third previous study of this type, Lecendreux et al. (2017), studied T cell subsets in a group of children and adolescents an average of 1.6 years after NT1 onset. Thirteen Pandemrix™-vacci- nated and 15 unvaccinated NT1 patients were compared with 32 controls of unknown vaccination and HLA status. They found an increased frequency of central memory CD4þT cells. In our study, as well as in Hartmann et al. (2016) and Moresco et al. (2018), there were no significant changes in this T cell subset between patients and controls. As can be seen inFig. 2, both HLA and vaccination status of the control cohort (the siblings) can cause shifts in the CD4þT cell composition, which might explain the discrepancies between our study and the previous studies. As described above, none of the three previous studies reported or knew the vaccina- tion status of their control cohort and two of the three studies also did not control for HLA status. The study discrepancies in cell fre- quencies could also have arisen from differences in the methods used: although this and two other studies [30,31] used flow cytometry with PBMCs, the choice of different commercially manufactured antibodies, and the slight differences in gating method, may have influenced the outcomes.
When looking into the T cell activation markers CD25 and CD69, Lecendreux et al. (2017) found higher levels of CD4þT cells positive for CD25 and CD69 and higher levels of CD8þT cells positive for CD69 in NT1 patients compared with controls. Hartmann et al.
(2016) found higher levels of the CD69 marker in the differentiated naïve CD4þT cell subset in patients compared with controls [29].
We did not replicate any of thesefindings, but instead we showed that in our sibling control group the levels of CD8þCD25þT cells varied with vaccination status and CD4þCD25þT cells varied with HLA-status. Lecendreux et al. (2017) reported decreased levels of CD8þCD25þT cells in vaccinated patients compared with unvac- cinated patients [30]. This demonstrates that knowing the vacci- nation and HLA status could be important when comparing T cell subsets in NT1 to controls. However, it is important to note that we have not corrected for multiple comparisons, and that our study was not designed to compare vaccinated and unvaccinated non- narcoleptic controls, so we cannot draw any firm conclusions about this. Unreported infections, such as common seasonal flu, could also have important effects. Bias could have been introduced into the data if patients and controls were not collected in parallel but instead, for instance, at different times of the year. A strength of our study is that the samples were collected strictly in parallel, and that the controls were from the same household as the patients, and thereby likely to have been exposed to the same circulating pathogens. We also considered information on medication use of all participants. We excluded those with acute infections and those who were taking systemic anti-inflammatory or immunosuppres- sive medication. Effects from unreported medication (eg, steroids and anti-inflammatory drugs) or acute infections in other study cohorts (patients and controls) could introduce variation into the responses of the patients studied.
A limitation of our study is that we did not include unrelated controls. However, for this type of study, we regard siblings to be good, or even better, controls than unrelated individuals. The concordance of NT1 in monozygotic twins is approximately 25%, signifying that genetic makeup is an important factor, but also suggesting that a variety of environmental factors contribute to the attainment of a threshold above which the disease develops. Since only a few environmental factors are known to be associated with narcolepsy [14,20], we tried to reduce this unknown effect by using siblings as controls in comparisons, because by being in the same household they can broadly be assumed to have been exposed to the same environmental factors as the patients. In addition, we have scrutinized siblings as closely as the patients to gain knowl- edge about them (ie, their vaccination status, presence of NT1 and other diseases, medication use, HLA status etc.).
Importantly, we did not investigate specific T cell auto- reactivities in this study. We cannot on the basis of our result say anything about the presence of autoreactive T cells or T cells with specificity towards a vaccine or virus.
In this study, we aimed to understand whether a general disease specific T cell signature is present in patients with NT1. Such signature could be a useful biomarker for tracking disease devel- opment or treatment response. Indeed, we did confirm that NT1 patients have fewer effector memory CD4þ T cells compared to their non-narcoleptic siblings, but only when controlling for HLA DQB1*06:02 and vaccination status. Previously it has been shown that the same T cell subset is also decreased in NT1 patients compared to unrelated healthy individuals [29]. This strongly supports that what we report is a genuine biological phenomenon.
We cannot, based on our data, explain why CD4þT cells composi- tion is different in the NT1 patients. It could be linked to the pro- posed autoimmune pathogenesis, but is perhaps more likely a consequence of having a sleep disorder as it has previously been shown that T cell levels are highly dependent on sleep [47,48], so the changed sleep-wake pattern in NT1 could be causing the shift we see in CD4þT cell subsets. Our patients were unmedicated and in the light of ourfinding, it would be interesting to study whether the CD4þT cell distribution normalises in well medicated patients.
5. Conclusion
In conclusion, we found that NT1 is associated with lower levels of effector memory CD4þT cells but only when additionally con- trolling for HLA DQB1*06:02 and H1N1 (Pandemrix™) vaccination status in both patients and controls. Importantly, thefinding of low effector memory CD4þT cells in NT1 is an independent replication of a previous similarfinding supporting that it is indeed a genuine biological phenomena. We further demonstrate the importance of carefully characterizing patients as well as controls including HLA and vaccination status when studying T cell subsets in NT1.
Funding
During conduct of the study, RV reports grant from South- Eastern Norway Regional Health Authority (grant 2017070) and SKH reports funding from The Norwegian Ministry of Health and Care Services. BAL, MKV and TR have no financial interests to disclose. Non-financial declarations of interests: none.
Author contribution
Rannveig Viste, Conceptualization, Methodology, Validation, Formal analysis, Investigation, Writingeoriginal draft, Writinge review&editing, Visualization. Benedicte A. Lie, Conceptualization, Methodology, Writingeoriginal draft, Writingereview&editing, Supervision. Marte K. Viken, Methodology, Investigation, Writinge review&editing. Terje Rootwelt, Conceptualization, Methodology, Writingeoriginal draft, Writingereview&editing, Supervision.
Stine Knudsen-Heier, Conceptualization; Methodology, Validation, Investigation, Writingeoriginal draft, Writingereview&editing, Supervision, Project administrator. Birgitte R. Kornum, Conceptu- alization, Methodology, Validation, Formal analysis, Investigation, Writingeoriginal draft, Writingereview&editing, Supervision, Project administrator.
Disclosures
RV is supported by a South-Eastern Norway Regional Health authority grant (2,017,070), SKH has received research support from the Norwegian Ministry of Health and Care Services and BRK reports being a founder of Ceremedy ApS and consulting for Orexia Therapeutics, UCB Pharma and Lundbeck. BAL, MKV and TR report no disclosures.
Acknowledgements
Above all, we wish to thank all the patients and their families who participated in our study. We also thank Ranveig Østrem, for harvesting and preserving cells from the blood samples; Helle Kingaaard Lilja-Fischer for assistance duringflow cytometry labo- ratory work; Lau Fabricius Larsen for valuable help during flow cytometry analysis; the staff at the Norwegian Sequencing Centre (https://sequencing.uio.no/) for contributing to the HLA typing;
David Swanson for assistance in analyses and interpretation of statistical outputs; Janita Vevelstad, Hilde T. Juvodden, and Sebjørg E. H. Nordstrand for administering family inclusion; and Phil Mason for editing the English text.
Conflict of interest
None declared.
The ICMJE Uniform Disclosure Form for Potential Conflicts of Interest associated with this article can be viewed by clicking on the following link:https://doi.org/10.1016/j.sleep.2021.07.024.
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://doi.org/10.1016/j.sleep.2021.07.024.
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