Immunologic profiles of multiple sclerosis treatments ... · variants for multiple sclerosis (MS),...

James Dooley MScIne Pauwels PhDDean Franckaert MScIde Smets MDJosselyn E Garcia-Perez

MScKelly Hilven MScDina Danso-Abeam PhDJoanne Terbeek MDAnh TL Nguyen PhDLouis De Muynck PhDBrigitte Decallonne MD

PhDBeacuteneacutedicte Dubois MD

PhDAdrian Liston PhDAn Goris PhD

Correspondence toDr Gorisangoriskuleuvenbeor Dr Listonadrianlistonvib-kuleuvenbe

Supplemental dataat Neurologyorgnn

Immunologic profiles of multiple sclerosistreatments reveal shared early B cellalterations

ABSTRACT

Objective We undertook a systems immunology approach of the adaptive immune system in mul-tiple sclerosis (MS) overcoming tradeoffs between scale and level of detail in order to identify theimmunologic signature of MS and the changes wrought by current immunomodulatorytreatments

Methods We developed a comprehensive flow cytometry platform measuring 38 immunologiccell types in the peripheral blood of 245 individuals in a routine clinical setting These includepatients with MS untreated or receiving any of 4 current immunomodulatory treatments(interferon-b glatiramer acetate natalizumab or fingolimod) patients with autoimmune thyroiddisease and healthy controls

Results An increase in memory CD81 T cells and B cells was observed in untreated patients withMS Interferon-b and fingolimod induce significant changes upon multiple aspects of the periph-eral immune system with an unexpectedly prominent alteration of B cells Overall both treat-ments push the immune system in different directions with only 2 significant effects sharedacross these treatmentsmdashan increase in transitional B cells and a decrease in class-switched Bcells We further identified heightened B cell-activating factor (BAFF) levels as regulating thisshared B cell pathway

Conclusions A systems immunology approach established different immunologic profiles inducedby current immunomodulatory MS treatments offering perspectives for personalized medicinePathways shared between the immunologic architecture of existing efficacious treatments iden-tify targets for future treatment design Neurol Neuroimmunol Neuroinflamm 20163e240 doi

101212NXI0000000000000240

GLOSSARYAITD5 autoimmune thyroid disease BAFF5 B cell-activating factormDC5myeloid dendritic cellMS5multiple sclerosisNMO 5 neuromyelitis optica PBMC 5 peripheral blood mononuclear cell RTE 5 recent thymic emigrant

The emergence of high-throughput genetics technology led to the identification of 100 riskvariants for multiple sclerosis (MS) reinforcing the key role for adaptive immunity12 The basisfor understanding the immunology of MS is by contrast still largely founded upon animalmodels where intrinsic limitations in the fidelity of models to disease processes interspeciesbarriers and the highly complex nature of MS have hampered translational potential3 Despiteprogress in the treatment of MS the predictive capacity for successful treatments remains poorwith a trial and error approach being required and the precise mechanism of action oftenremains unclear34 These observations have spurred the call for characterization of the immunesystem in MS and upon treatment35

These authors contributed equally to this work

From the Department of Immunology and Microbiology (JD DF JEG-P DD-A ATLN AL) Laboratory for NeuroimmunologyDepartment of Neurosciences (IP IS KH B Dubois AG) Laboratory for Neurobiology Department of Neurosciences (LDM)Laboratory for Clinical and Experimental Endocrinology Department of Clinical and Experimental Medicine (B Decallonne) and Department ofNeurology University Hospitals Leuven (IS JT B Dubois) KU LeuvenndashUniversity of Leuven and Center for the Biology of Disease (JDDF JEG-P DD-A ATLN AL) VIB (LDM) Leuven Belgium

Funding information and disclosures are provided at the end of the article Go to Neurologyorgnn for full disclosure forms The Article ProcessingCharge was paid by the authors

This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License 40 (CCBY-NC-ND) which permits downloading and sharing the work provided it is properly cited The work cannot be changed in any way or usedcommercially

Neurologyorgnn copy 2016 American Academy of Neurology 1

ordf 2016 American Academy of Neurology Unauthorized reproduction of this article is prohibited

In-depth analysis of variation in the adap-tive immune system in humans has proven tobe difficult due to trade-offs between scaleand level of detail Large-scale flow cytometryscreens have now been able to characterizeimmune cells in the peripheral blood ofhealthy controls6ndash8 We have here applied thissystems immunology approach to the studyof MS and for comparison autoimmune thy-roid disease (AITD) characterized by familialclustering and shared genetic risk factors withMS910 In an unbiased analysis we revealedthe immunologic signatures of MS and 4 cur-rent immunomodulatory treatments Theprominent alterations in B cell subsets mostimportantly the increase in B cell-activatingfactor (BAFF) and transitional B cells inducedby both interferon-b and fingolimod indi-cate the importance of the early B cell path-way in treating MS

METHODS Study population Unrelated patients of Cauca-sian descent fulfilling McDonald criteria for MS or criteria for

clinical AITD and spouses as healthy controls were included

in the study over a 22-month inclusion period (table 1)

Extensive demographic and clinical data were collected through

a questionnaire and medical records Exclusion criteria were

cancer immunosuppressive treatments antibiotics anti-allergy

or anti-inflammatory treatment in the week prior to sampling

and for healthy controls presence of known clinical autoimmune

disease

Standard protocol approvals registrations and patientconsents Participants gave written informed consent and the

study was approved by the Ethics Committee of the University

Hospitals Leuven

Immunophenotyping and cytokine measurements Periph-eral blood mononuclear cells (PBMCs) and plasma were isolated

from heparinized blood and stored at 280degC prior to analysis A

multiplex flow cytometry platform previously validated in

healthy controls8 was applied (table e-1 and figure e-1 at

Neurologyorgnn) Some variables were measured in subsets of

the samples only Measurements are expressed as percentage of

parental or grandparental cells as indicated BAFF plasma levels were

measured using a human BAFF Quantikine ELISA (RampD Systems

Minneapolis MN) Averages were taken over 2ndash3 replicates after

standardization using samples present on multiple plates Sensitivity

was 644 pgmL and average standard deviation 15

Gene expression RNA was extracted from total PBMCs

and reverse transcribed using a high-capacity cDNA reverse

transcription kit (Life Technologies Carlsbad CA) Droplet digital

PCR (Bio-Rad Hercules CA) with gene expression assays (Life

Technologies) for the BAFF gene TNFSF13B (Hs00198106_m1)

and housekeeping gene POLR2A (Hs00172187_m1) was performed

using 4 ngmL cDNA Relative quantity of TNFSF13B vs POLR2Awas measured with QuantaSoft v14 (Bio-Rad) Correlation between

separate experiments (n 5 68) was 075

Statistical analysis For ratios of variables the natural logarithmwas taken Spearman correlation for pairs of variables and signif-

icance in correlation coefficient between groups were calculated

and plotted with heatmap2 and cocor packages Linear regression

models in R 2141 included the immunologic variable as func-

tion of disease or treatment and covariates sex age and for dis-

ease effects disease duration at sampling Multiple testing

correction was applied for 38 variables across 4 treatments (p 5

000033) Nonmetric multidimensional scaling was used to

Table 1 Properties of the study population

Characteristics Controls AITD MS

Total no of participants 36 55 154

Female 39 84 68

Age at onset mean (range) y mdash 38 (15ndash72) 32 (10ndash53)

Age at sampling mean (range) y 47 (19ndash72) 43 (20ndash73) 42 (21ndash70)

Disease duration at sampling mean (range) y mdash 4 (0ndash58) 11 (0ndash41)

Disease type AITD ( Hashimoto thyroiditis) mdash 15 mdash

Disease course MS ( primary progressive) mdash mdash 8

Multiple Sclerosis Severity Scale mean (range) mdash mdash 308 (003ndash986)

Concurrent AITD n mdash mdash 10

Current treatment n

Interferon-b mdash mdash 54

Glatiramer acetate mdash mdash 21

Natalizumab mdash mdash 9

Fingolimod mdash mdash 14

None mdash mdash 56

Duration treatment at sampling mean (range) y mdash mdash 4 (0ndash17)

Abbreviations AITD 5 autoimmune thyroid disease MS 5 multiple sclerosis

2 Neurology Neuroimmunology amp Neuroinflammation


visualize dissimilarities of samples between treatments The ordi-

nation was created in R 310 using R package vegan with custom

scripts Distance matrix was calculated with Bray-Curtis

dissimilarity index on original data To test for the contribution

of each variable to the resulting distance matrix we applied

Mantel test with 999 permutations comparing the original

distance matrix to one with one variable removed at a time

RESULTS The adaptive immune profile of MS Inorder to directly study the adaptive immune systemacross conditions we applied a systems immunologyapproach in 154 patients with MS 36 controls andfor comparison 55 patients with AITD (table 1) Foreach individual the frequency of 38 leukocyte pop-ulations or ratios was assessed in the peripheral bloodutilizing multiparameter flow cytometry with a focuson T- and B cell subsets (table e-1 and figure e-1)Phenotypendashphenotype correlations were assessedacross each group (figure 1) identifying coregulatedleukocyte populations that validate the systemsimmunology approach used here as demonstratedpreviously8 Treatment of MS resulted in substantialimmunologic deviation (described below) so initial

analysis was performed on untreated patients withMS Comparison of the immunologic status of pa-tients with AITD currently untreated or treated withthe thyroperoxidase inhibitor methimazole revealedno consistent differences (data not shown) allowingmerged analysis Of the robust immunologic changesobserved to occur in autoimmune disease patientscompared to healthy individuals there were surpris-ingly no overlaps between AITD and MS (table e-2)MS was correlated with perturbation in the CD81

T-cell compartment compared to healthy controls witha shift towards effector memory CD81 T cells(CD42CD81CD45RA2CCR72) as a percentage ofall CD81 T cells (p 5 0012) and increased the pro-portion of B cells resulting in a decreased TB cell ratioThe increase in B cells was mainly due to an increase inmemory B cells (CD42CD191IgM1CD271) as a per-centage of total lymphocytes (p 5 00042) and wasespecially prominent early on in disease (figure 2 A andB and table e-2) Disease course (bout onset or primaryprogressive) time since last relapse and multiple scle-rosis severity scores did not confound these observations

Figure 1 The human adaptive immune profile in multiple sclerosis (MS)

In A and B the right upper half above the diagonal indicates coregulation between pairs of cell types in healthy controls (n 5 36) (red positive correlationcoefficient blue negative correlation coefficient light gray no data available) Unbiased clustering of coefficients was performed to group coregulated celltypes Upon clustering a main distinct naive cluster was observed consisting of coregulated CD41 T cells CD41CD81 ratio and naive T cells together withrecent thymic emigrants (RTE) of both CD41 and CD81 lineages This naive cluster was negatively correlated with activated and antigen-experiencedlymphocyte subsets Several microclusters were additionally observed with coregulation of regulatory T cells (Tregs) with central memory CD41 and CD81 Tcells (the antigen-experienced microcluster) coregulation of Th1 cells and interferon-g-producing CD81 cells (the Th1 microcluster) coregulation of Th2 andmemory B cells (the Th2 microcluster) and so forth revealing the emergence of known immunologic interactions through this systems immunologyapproach In the lower left half below the diagonal dark gray indicates coregulation between pairs of cell types in (A) patients with untreated MS (MS_UNTn5 56) and (B) patients with autoimmune thyroid disease (AITD n5 55) that does not differ significantly from healthy controls Coregulation between pairsof cell types that is significantly altered by disease (p 005 and boxed if p 001) in (A) untreated patients with MS vs controls and (B) patients with AITDvs controls is colored (red positive correlation coefficient blue negative correlation coefficient light gray no data available)

Neurology Neuroimmunology amp Neuroinflammation 3


(data not shown) The relationship between differentimmunologic populations is largely left intact in pa-tients with MS but the positive coregulation betweenB cells and the naive CD41 T-cell cluster disappeared(r controls 5 037 r MS 5 2036 p 5 000064)(figure 1A) Four immunologic variables were associ-ated with nominal significance with AITD but notMS increased CD41 recent thymic emigrant (RTE)(p5 0047) and Th17 (p5 0046) cells as percentageof CD41 T cells and increased transitional (p5 0046)with decreased switched B cells as percentage of B cells(p 5 00019) (figure 2 CndashF) A Th17-positivecoregulation with effector memory CD41 T cells(r controls 5 2016 r AITD 5 051 p 5 00092)and negative coregulation with the CD41-naive cluster(r controls 5 0093 r AITD 5 20483 p 5 0027)appeared in patients with AITD that was not presentin healthy individuals or patients with MS (figure 1B)indicating greater influence of Th17 cells over theimmunologic landscape in AITD

The immunologic profile induced by MS treatments

After establishing the immunologic changes inducedby MS in untreated patients we investigated theimmunologic signature induced by 4 common immu-nomodulatory treatments for MS (table e-3) Glatir-amer acetate (Copaxone Teva PharmaceuticalsCastleford UK n 5 21) and natalizumab (Tysabri

Biogen Idec Maidenhead UK n5 9) induced severalimmunologic changes reaching nominal significanceincluding an increase in the frequency of RTE CD41

T cells (p 5 0045) with glatiramer acetate and ofswitched B cells (p 5 0023) upon treatment withnatalizumab however none of these changes survivedmultiple testing (152 tests corresponding to p 5

000033)Interferon-b (Avonex Biogen Idec Maidenhead

UK Betaferon Bayer Pharma AG Berlin GermanyRebif Merck Serono London UK n 5 54) and fin-golimod (Gilenya Novartis Pharma AG HorshamUK n 5 14) on the other hand were observed toalter multiple aspects of the peripheral immune systemboth in a multidimensional analysis including all 38variables (figure 3) and for individual variables (tablee-3) A total of 4 variables regulated by treatment withinterferon-b survived multiple testing (p 000033)(figure 4 AndashD) These include 2 changes in frequencyof the B cell population with an increase in transitionalB cells (p 5 000030) and decrease in switched B cells(p 5 80E-05) The final significant changes werea decrease in frequency of myeloid dendritic cells(mDCs) (p 5 922E-06) and interferon-g-producingCD81 cells (p 5 000032) with an additional 12 var-iables reaching nominal significance (p 005) (tablee-3) including an increase in total (p 5 00064) andnaive (p 5 000037) B cells and a decrease in Th1

Figure 2 Distinct changes to immunoprofile in autoimmune thyroid disease (AITD) and multiple sclerosis (MS)

A linear regression with covariates age sex and disease duration was applied to the immune profiling results of patients with AITD and untreated patientswith MS vs healthy controls andmdashwithin patientsmdashuntreated MS vs AITD Significant differences in the peripheral immune system of untreated patientswith MS compared to controls were restricted to (A) effector memory CD81 cells and (B) memory B cells Significant differences compared to controlsobserved for patients with AITD but not patients with MS include altered proportions of (C) recent thymic emigrant CD41 (D) Th17 (E) transitional B cellsand (F) class-switched B cells Median with boxes indicate 25th and 75th percentile and whiskers indicate 15 3 interquartile range



(p5 00014) The decrease in mDCs and in Th1 cellsis correlated with the increase in B cells (p5 0023 andp 5 0033 respectively) suggesting the B cell changesas primary drivers in the interferon-b-driven immunedeviation

Fingolimod induced the strongest changes in theperipheral immune system of the 4 routine MS treat-ments (figure 3) with changes in the frequency of1338 of the measured immunologic variables survivingmultiple testing (p 000033) (figure 4) and another14 reaching nominal significance (p 005) (table e-3)Within the T-cell compartment the observed reduc-tions in the frequency of C-chemokine receptor type7ndashexpressing naive and central memory populationswere consistent with the biological function for fingoli-mod11 but within the effector population Th2 cellsproved relatively refractory to fingolimod compared toTh1 Th17 and Tfh cells (table e-3 figure e-2) Com-pared to the decrease in the T-cell compartment theobserved decrease in B cell frequency (p 5 116E-10)(figure 4E) was however more profound These alter-ations were driven by reduced switched (p 5 000014)and naive (p 5 644E-09) B cells (figure 4 B and G)with transitional B cells (p5 00012) and plasmablasts(p 5 350E-09) (figure 4 A and H) increased as

a proportion of B cells but remaining constant as a pro-portion of total lymphocytes (figure e-3)

Early B cell changes as shared immunologic alterations

across treatments At a global level the 2 strongestimmunomodulatory treatments pushed the immunesystem in different directions (figure 3) with only 2significant effects shared across treatmentsmdasha decreasein switched B cells and an increase in transitional B cellsas percentage of total B cells upon treatment with bothinterferon-b and fingolimod (figure 4 A and B) AsBAFF drives the differentiation of transitional Bcells1213 we additionally measured levels of BAFF inthe same individuals We observed upregulated BAFFplasma levels for the AITD disease process (p 5

00011) In MS levels were unaltered in untreated pa-tients but were upregulated during treatment withinterferon-b (high-dose p5 269E-09) and fingolimod(p 5 217E-10) in parallel with changes in the B cellcompartment (figure 5 AndashC) Treatment-inducedchanges followed a dose-dependent model (forinterferon-b) (figure 5 AndashC) and decreased byincreased treatment duration (data not shown)Changes in BAFF plasma levels were correlated withthe observed changes in B cell immunophenotype ie

Figure 3 Multiple sclerosis (MS) immunomodulatory treatments interferon-b (IFNB) and fingolimod (FTY720)result in global perturbation of the immune system

Patients with MS being treated with one of 4 immunomodulatory treatments (GA5 glatiramer acetate NAT5 natalizumab)were plotted together with controls (CON) and untreated (UNT) patients with MS using nonparametric multidimensionalscaling over 38 immunologic variables Individual patients and distance from the average of each condition are shownVariation explained by each axis is indicated in the parentheses Pairwise distance of samples was calculated based on Bray-Curtis dissimilarity index



Figure 4 Shared and unique immune changes induced by multiple sclerosis (MS) immunomodulatorytreatments

The effect of 4 immunomodulatory treatments (interferon-b [IFNB] glatiramer acetate [GA] natalizumab [NAT] fingolimod[FTY720]) was compared with combined controls (CON) and untreated (UNT) patients with MS after establishing nosignificant difference between the latter 2 groups (except for panels E and F) A linear regression with covariates age

Continued



the increase in the frequency of transitional B cells(r2 5 030 p 5 00047) and decrease in switched Bcells (r2 5 0072 p 5 0022) as percentage of B cellsafter accounting for diseasetreatment group sex andage (figure 5 DndashE) In line with protein levelstranscription levels of the BAFF gene (TNFSF13B)in total PBMCs were upregulated in patients withAITD (p 5 0046) as well as upon treatment ofpatients with MS with high-dose interferon-b (p 5

0035) or fingolimod (p 5 000087) (figure 5F)

DISCUSSION In this study we have undertakena comprehensive and unbiased analysis of the adaptiveimmune system measuring 38 immunologic variablesin 245 individuals Our approach allows us to directlycompare on the same large-scale platform MS and

AITD 2 distinct autoimmune diseases with elementsof shared genetic risk910 as well as 4 commonimmunomodulatory treatments for MS (interferon-bglatiramer acetate natalizumab fingolimod) of whichthe mechanism of action is not fully understood34

Patients with MS displayed systematic immune de-viations with an overall increase in effector memoryCD81 T cells and memory B cells Both cell typeshave recently been reported as part of the inflammatoryresponse in MS1415 and as populating the CNS inMS16ndash18 providing a biological parallel to thesesystemsndashimmunology associations Despite the sharedgenetic risk factors the immunologic deviationsobserved for MS were distinct from AITD This resultopposes a model (implied from genome-wide associa-tion studies) where common immunologic processes

and sex was applied Significant differences (after multiple testing correction) in the peripheral immune system of patientswith MS following treatment compared to controls and untreated patients with MS included altered proportions of (A)transitional B cells (B) switched B cells (C) myeloid dendritic cells (mDC) (D) interferon-g-producing CD81 T cells (E) B cells(F) T cellB cell ratio (G) naive B cells (H) plasmablasts (I) CD41CD81 T cell ratio (J) Th2 cells (K) interleukin-2 (IL-2)ndashproducing CD41 T cells (L) CD81 terminally differentiated effector memory T cells (TEMRA) (M) IL-2-secreting CD81 T cellsand (N) natural killer T cell (NKT) cells Median with boxes indicating 25th and 75th percentile and whiskers indicating15 3 interquartile range

Figure 4 legend continued

Figure 5 Increased B cell-activating factor (BAFF) levels are shared between immunomodulatory treatments

(A) Plasma BAFF levels (B) transitional B cells (C) switched B cells and (F) total peripheral blood mononuclear cells (PBMC) BAFF gene expression levels(RQ 5 relative quantity compared to housekeeping gene with addition of n 5 13 additional controls not part of the immunophenotyping cohort) werequantified in controls (CON) patients with autoimmune thyroid disease (AITD) and patients with multiple sclerosis (MS) either untreated (MS_UNT) or treatedwith 4 immunomodulatory treatments (interferon [IFN]ndashb low and IFN-b high 5 IFN-b low or high dose GA 5 glatiramer acetate NAT 5 natalizumabFTY720 5 fingolimod) Median with boxes indicating 25th and 75th percentile and whiskers indicating 15 3 interquartile range A linear regression withcovariates age and sex was applied Correlation between plasma BAFF levels and (D) transitional B cells and (E) switched B cells in the entire cohort afteraccounting for diseasetreatment group age and sex



underlie different autoimmune diseases with theunique clinical manifestations being based on the spec-ificity of the escaping forbidden clones By contrastthe results here support a more complex genendashimmunerelationship where largely overlapping genetic poly-morphisms nevertheless synergize to form immuno-logic deviations that are distinct at the systems level

In addition to the different efficacy and safety pro-file of the 4 compounds in routine MS treatment eachinduced unique constellations of immune deviationswhich offers perspectives to the challenge of personal-ized medicine5 Alterations in B cells were unexpect-edly prominent upon treatment indeed the onlyshared treatment effects were notably B cell-relatedOur observations on the crucial role of B cells inimmunomodulatory treatment of MS hence add toemerging evidence emphasizing the importance of Bcells which have long stood in the shadow of T cells inboth MS pathogenesis and treatment19

Our immunophenotyping platform suggests a janusrole for BAFF in autoimmune disease and treatmentThe pathogenic face of BAFF is exposed in AITDwhere BAFF is upregulated and may contribute toTh17-mediated disease By contrast the protective faceof BAFF is revealed as the convergence point of effec-tive immunomodulatory treatment in MS Here weconfirm previously reported changes in BAFF proteinlevel upon interferon-b treatment20 and establish itas a unique shared mechanism with fingolimod Thispathway is furthermore shared with promising emerg-ing lymphocyte and B cell depletion therapies forMS2122 We demonstrate that these protein levelchanges are not merely due to reduced consumptionby BAFF receptors on B cells but involve active upre-gulation of transcription Both in AITD and uponimmunomodulatory treatment of MS we now corre-late BAFF plasma changes to an increase in transitionaland decrease in switched B cells as percentage of B cellsand propose the BAFF pathway as the mechanism ofaction driving these B cell alterations Transitional Bcells may be enriched for autoreactive B cells and havebeen implicated in the pathogenesis of other autoim-mune diseases such as Sjoumlgren syndrome and systemiclupus erythematosus23 At the same time they may alsohave regulatory properties supporting a beneficial effectas part of the therapeutic mechanisms of MS immu-nomodulatory treatments24

BAFF antagonists have been proposed as a promis-ing strategy based on animal models for MS2526 How-ever 2 clinical trials in MS with atacicept neutralizingall forms of BAFF and the related a proliferation-inducing ligand (APRIL) had to be stopped prema-turely because of increased inflammatory activity inpatients withMS and a 2-fold higher rate of conversionfrom clinically isolated syndrome to clinically definiteMS in the treated compared to placebo group2728 A

third trial with a monoclonal antibody against BAFF(tabalumab) was completed but no results are avail-able29 Of note animal models leading to these clinicaltrials had a Th17-mediated component26 which in ourstudy we observe in human patients with AITD but notMS The immunomodulatory treatments for which weobserve an increase in BAFF interferon-b and fingoli-mod have notably distinct effects between MS wherethey are beneficial and the neuroinflammatory diseaseneuromyelitis optica (NMO) where these treatmentsare not only ineffective but may be harmful and resultin excessive inflammatory activity and increased relapserate and disability3031 This is in line with our observa-tion that the unique shared signature of both treatmentsis an increase in BAFF coupled to already increasedlevels in BAFF seen in NMO but not MS32 We pro-pose that the distinct and shared immunologic archi-tecture of disease and of existing efficacious treatmentsmay inform further design of novel treatment strategiesIn particular our data suggest that antagonism of BAFFmay be counterproductive to MS treatment but may befurther pursued in NMO where current immunosup-pressive or immunomodulatory treatments are onlypartially effective33

Our study was based on a routine clinical settingin a tertiary outpatient clinic While we correctedfor heterogeneity in age and sex additional variablesaffecting treatment decisions patient complianceand treatment response are potential confoundersPreexisting variation among the immune profiles ofpatients with MS is however unlikely to be respon-sible for the immunologic responses to treatmentWhile patients with MS were assigned to treatmentgroups based on standard clinical criteria (driven bydisease factors) assignment between low-doseinterferon-b high-dose interferon-b and glatirameracetate was determined by patient-preferred regimena research design that would not produce the dose-dependent effects observed with interferon-b or thedistinct immunologic changes between interferon-band glatiramer acetatendashtreated groups Likewise ofthe 14 fingolimod patients 10 were included as partof a randomized clinical trial determined by patientpreference for an oral treatment a design structurethat avoids segregation based on preexisting clinicalvariation Furthermore our recapitulation of previ-ously reported findings in studies of single treatmentstypically limited by sample size and number of celltypes investigated34ndash38 validates the methodology andthus the novel associations also observed in this sys-tems immunology approach While we were only ableto assess changes in the peripheral blood and not thetarget tissue there is active exchange between theCNS and peripheral blood1839 and changes inthe peripheral blood have previously been shown tobe able to capture genetic variation important for



MS40 Moreover immunomodulatory treatments arenot administered directly into the CNS and thus thelikely location of activity is in the periphery whereour analysis took place

In response to the challenge put forward for large-scale evaluation of the adaptive immune system in pa-tients with MS3 we demonstrate that a comprehensivecommon immunophenotyping platform is able to dis-sect the unique immunologic signatures of MS andimmunomodulatory treatments The different effectsof immunomodulatory treatments suggest that theimmunologic profile may in the future assist the neu-rologist in taking treatment decisions and optimizingthe efficacy and safety for subgroups of patients henceoffering perspectives to the challenge of personalizedmedicine in MS5 We propose that further design ofnovel treatment strategies takes into account the sharedimmunologic architecture of existing efficacious treat-ments such as the early B cell changes with increase inBAFF and transitional B cells

AUTHOR CONTRIBUTIONSJD IP DF IS JEG-P KH DD-A and LDM performed

experiments IS JT ATLN and AG performed statistical analyses

B Decallonne and B Dubois provided samples and clinical data JD

IP B Decallonne B Dubois AL and AG designed the experiment

AL and AG supervised the experiment and wrote the first draft of the

manuscript All authors contributed to data interpretation and writing of

the manuscript

ACKNOWLEDGMENTThe authors thank the patients and their relatives for participating in this

study Cindy Thys Katleen Clysters and Klara Mallants for assistance in

sample collection and management and Dr V Lagou Dr S Humblet-

Baron and Prof P Dupont for discussions

STUDY FUNDINGB Decallonne and B Dubois are Clinical Investigators of the Research

Foundation Flanders (FWO-Vlaanderen) This project was supported by

the Research Fund KU Leuven (OT11087 to B Dubois and AG)

Research Foundation Flanders (G073415N to AG and B Dubois) MS-

Liga Vlaanderen (to AL and AG) Belgian Charcot Foundation (to

AG and IS) and ERC Start Grant IMMUNO (to AL)

DISCLOSUREJ Dooley reports no disclosures I Pauwels is employed by Ismar Health-

care D Franckaert received research support from Becton-Dickinson and

his partner is an ex-employee of Boehringer-Ingelheim and current

employee of Becton-Dickinson I Smets received travel funding from

Biogen Idec and Boehringer and received research support from

the Belgian Charcot Foundation J Garcia-Perez K Hilven and

D Danso-Abeam report no disclosures J Terbeekrsquos spouse is employed

by and received travel funding from Janssen Pharmaceuticals and received

a fellowship from Research Foundation Flanders (FWO) ATL Nguyen

reports no disclosures L De Muynck is employed by Janssen RampD

B Decallonne reports no disclosures B Dubois served on the advisory

boards for Biogen Idec and Merck received travel funding from Novartis

Merck Serono BSP Sanofi-Aventis and Biogen Idec and received

research support from Serono Biogen Idec Teva and Novartis A Liston

is deputy editor for Immunology and Cell Biology and Clinical and Trans-

lational Immunology is on the editorial board for Frontiers in Immune

Tolerance his spouse is an ex-employee of UCB and he received research

support from JDRF European Research Council Research Foundation

Flanders (FWO) KU Leuven VIB Interuniversity Attraction Poles

Jeffrey Modell Foundation and Juvenile Diabetes Research Foundation

A Goris received research support from Research Foundation Flanders

(FWO) Belgian Charcot Foundation Belgian Neurological Society and

Wetenschappelijk Onderzoek Multiple Sclerose Go to Neurologyorgnn

for full disclosure forms

Received December 10 2015 Accepted in final formMarch 28 2016

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13 Jacobi AM Huang W Wang T et al Effect of long-term

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controlled dose-ranging study Arthritis Rheum 200962

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14 Haegele KF Stueckle CA Malin JP Sindern E Increase

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pared to healthy controls J Neuroimmunol 2007183

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15 Seifert M Przekopowitz M Taudien S et al Functional

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Proc Natl Acad Sci USA 2015112E546ndashE555

16 Battistini L Piccio L Rossi B et al CD81 T cells from

patients with acute multiple sclerosis display selective increase



of adhesiveness in brain venules a critical role for P-selectin

glycoprotein ligand-1 Blood 20031014775ndash4782

17 Ifergan I Kebir H Alvarez JI et al Central nervous sys-

tem recruitment of effector memory CD81 T lympho-

cytes during neuroinflammation is dependent on alpha4

integrin Brain 20111343560ndash3577

18 Stern JN Yaari G Vander Heiden JA et al B cells pop-

ulating the multiple sclerosis brain mature in the draining

cervical lymph nodes Sci Transl Med 20146248ra107

19 Krumbholz M Derfuss T Hohlfeld R Meinl E B cells

and antibodies in multiple sclerosis pathogenesis and ther-

apy Nat Rev Neurol 20128613ndash623

20 Krumbholz M Faber H Steinmeyer F et al Interferon-beta

increases BAFF levels in multiple sclerosis implications for

B cell autoimmunity Brain 20081311455ndash1463

21 Lavie F Miceli-Richard C Ittah M Sellam J

Gottenberg JE Mariette X Increase of B cell-activating

factor of the TNF family (BAFF) after rituximab treat-

ment insights into a new regulating system of BAFF pro-

duction Ann Rheum Dis 200766700ndash703

22 Thompson SA Jones JL Cox AL Compston DA

Coles AJ B-cell reconstitution and BAFF after alemtuzu-

mab (Campath-1H) treatment of multiple sclerosis J Clin

Immunol 20103099ndash105

23 Vossenkamper A Lutalo PM Spencer J Translational

Mini-Review Series on B cell subsets in disease transitional

B cells in systemic lupus erythematosus and Sjogrenrsquos syn-

drome clinical implications and effects of B cell-targeted

therapies Clin Exp Immunol 20121677ndash14

24 Bouaziz JD Yanaba K Tedder TF Regulatory B cells as

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25 Huntington ND Tomioka R Clavarino C et al A BAFF

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tis PLoS One 20116e23629

27 Kappos L Hartung HP Freedman MS et al Atacicept in

multiple sclerosis (ATAMS) a randomised placebo-

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from a phase II randomized trial of the B-cell-targeting agent

atacicept in patients with optic neuritis J Neurol Sci 2015

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Mackay F The BAFFAPRIL system emerging functions

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517ndash522



DOI 101212NXI000000000000024020163 Neurol Neuroimmunol Neuroinflamm

James Dooley Ine Pauwels Dean Franckaert et al alterations

Immunologic profiles of multiple sclerosis treatments reveal shared early B cell

This information is current as of May 10 2016

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httpnnneurologyorgcgicollectionmultiple_sclerosisMultiple sclerosis

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2016 American Academy of Neurology All rights reserved Online ISSN 2332-7812Published since April 2014 it is an open-access online-only continuous publication journal Copyright copy

is an official journal of the American Academy of NeurologyNeurol Neuroimmunol Neuroinflamm

In-depth analysis of variation in the adap-tive immune system in humans has proven tobe difficult due to trade-offs between scaleand level of detail Large-scale flow cytometryscreens have now been able to characterizeimmune cells in the peripheral blood ofhealthy controls6ndash8 We have here applied thissystems immunology approach to the studyof MS and for comparison autoimmune thy-roid disease (AITD) characterized by familialclustering and shared genetic risk factors withMS910 In an unbiased analysis we revealedthe immunologic signatures of MS and 4 cur-rent immunomodulatory treatments Theprominent alterations in B cell subsets mostimportantly the increase in B cell-activatingfactor (BAFF) and transitional B cells inducedby both interferon-b and fingolimod indi-cate the importance of the early B cell path-way in treating MS

METHODS Study population Unrelated patients of Cauca-sian descent fulfilling McDonald criteria for MS or criteria for

clinical AITD and spouses as healthy controls were included

in the study over a 22-month inclusion period (table 1)

Extensive demographic and clinical data were collected through

a questionnaire and medical records Exclusion criteria were

cancer immunosuppressive treatments antibiotics anti-allergy

or anti-inflammatory treatment in the week prior to sampling

and for healthy controls presence of known clinical autoimmune

disease

Standard protocol approvals registrations and patientconsents Participants gave written informed consent and the

study was approved by the Ethics Committee of the University

Hospitals Leuven

Immunophenotyping and cytokine measurements Periph-eral blood mononuclear cells (PBMCs) and plasma were isolated

from heparinized blood and stored at 280degC prior to analysis A

multiplex flow cytometry platform previously validated in

healthy controls8 was applied (table e-1 and figure e-1 at

Neurologyorgnn) Some variables were measured in subsets of

the samples only Measurements are expressed as percentage of

parental or grandparental cells as indicated BAFF plasma levels were

measured using a human BAFF Quantikine ELISA (RampD Systems

Minneapolis MN) Averages were taken over 2ndash3 replicates after

standardization using samples present on multiple plates Sensitivity

was 644 pgmL and average standard deviation 15

Gene expression RNA was extracted from total PBMCs

and reverse transcribed using a high-capacity cDNA reverse

transcription kit (Life Technologies Carlsbad CA) Droplet digital

PCR (Bio-Rad Hercules CA) with gene expression assays (Life

Technologies) for the BAFF gene TNFSF13B (Hs00198106_m1)

and housekeeping gene POLR2A (Hs00172187_m1) was performed

using 4 ngmL cDNA Relative quantity of TNFSF13B vs POLR2Awas measured with QuantaSoft v14 (Bio-Rad) Correlation between

separate experiments (n 5 68) was 075

Statistical analysis For ratios of variables the natural logarithmwas taken Spearman correlation for pairs of variables and signif-

icance in correlation coefficient between groups were calculated

and plotted with heatmap2 and cocor packages Linear regression

models in R 2141 included the immunologic variable as func-

tion of disease or treatment and covariates sex age and for dis-

ease effects disease duration at sampling Multiple testing

correction was applied for 38 variables across 4 treatments (p 5

000033) Nonmetric multidimensional scaling was used to

Table 1 Properties of the study population

Characteristics Controls AITD MS

Total no of participants 36 55 154

Female 39 84 68

Age at onset mean (range) y mdash 38 (15ndash72) 32 (10ndash53)

Age at sampling mean (range) y 47 (19ndash72) 43 (20ndash73) 42 (21ndash70)

Disease duration at sampling mean (range) y mdash 4 (0ndash58) 11 (0ndash41)

Disease type AITD ( Hashimoto thyroiditis) mdash 15 mdash

Disease course MS ( primary progressive) mdash mdash 8

Multiple Sclerosis Severity Scale mean (range) mdash mdash 308 (003ndash986)

Concurrent AITD n mdash mdash 10

Current treatment n

Interferon-b mdash mdash 54

Glatiramer acetate mdash mdash 21

Natalizumab mdash mdash 9

Fingolimod mdash mdash 14

None mdash mdash 56

Duration treatment at sampling mean (range) y mdash mdash 4 (0ndash17)

Abbreviations AITD 5 autoimmune thyroid disease MS 5 multiple sclerosis








































Continued






























the manuscript







































2013451353ndash1360















242ndash256











20001231102ndash1111















201ndash210





168ndash174



















































201413353ndash363




351174ndash178








57ndash61
















nol 2014151127ndash135




1214ndash1221



















517ndash522




















Reprints









































Continued






























the manuscript







































2013451353ndash1360















242ndash256











20001231102ndash1111















201ndash210





168ndash174



















































201413353ndash363




351174ndash178








57ndash61
















nol 2014151127ndash135




1214ndash1221



















517ndash522




















Reprints































the manuscript







































2013451353ndash1360















242ndash256











20001231102ndash1111















201ndash210





168ndash174



















































201413353ndash363




351174ndash178








57ndash61
















nol 2014151127ndash135




1214ndash1221



















517ndash522




















Reprints














































201413353ndash363




351174ndash178








57ndash61
















nol 2014151127ndash135




1214ndash1221



















517ndash522




















Reprints





















Reprints




Immunologic profiles of multiple sclerosis treatments ... · variants for multiple sclerosis (MS),...

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