Neurofilament light chain level is a weak risk factor for ... · risk factor for the development of MS ABSTRACT Objective: To determine the prognostic value of selected biomarkers

ARTICLES

Georgina ArrambideMD PhD

Carmen Espejo PhDHerena Eixarch PhDLuisa M Villar PhDJoseacute C Alvarez-Cermentildeo

MD PhDCarmen Picoacuten MScJens Kuhle MDGiulio Disanto MD PhDLudwig Kappos MDJaume Sastre-Garriga

MD PhDDeborah Pareto PhDEva Simon BScManuel Comabella MD

PhDJordi Riacuteo MD PhDCarlos Nos MDCarmen Tur MD PhDJoaquiacuten Castilloacute MDAngela Vidal-Jordana MDIngrid Galaacuten MDMaria J Areacutevalo PhDCristina Auger MDAlex Rovira MDXavier Montalban MD

PhDDagger

Mar Tintore MD PhDDagger

Correspondence toDr Tintoremtintorecem-catorgor Dr Espejocarmenespejovhirorg

Editorial page 1068

Supplemental dataat Neurologyorg

Neurofilament light chain level is a weakrisk factor for the development of MS

ABSTRACT

Objective To determine the prognostic value of selected biomarkers in clinically isolated syn-dromes (CIS) for conversion to multiple sclerosis (MS) and disability accrual

Methods Data were acquired from 2 CIS cohorts The screening phase evaluated patients devel-oping clinically definite MS (CIS-CDMS) and patients who remained as CIS during a 2-year mini-mum follow-up (CIS-CIS) We determined levels of neurofascin semaphorin 3A fetuin A glialfibrillary acidic protein and neurofilament light (NfL) and heavy chains in CSF (estimated mean[95 confidence interval CI]) We evaluated associations between biomarker levels conversiondisability and magnetic resonance parameters In the replication phase we determined NfL levels(n 5 155) using a 900 ngL cutoff Primary endpoints in uni- and multivariate analyses wereCDMS and 2010 McDonald MS

Results The only biomarker showing significant differences in the screening was NfL (CIS-CDMS15531 [12087ndash18975] ngL and CIS-CIS 4990 [1688ndash8292] ngL p 00001) Thestrongest associations were with brain parenchymal fraction change (rs 5 20892) and percent-age brain volume change (rs 5 20842) at 5 years NfL did not correlate with disability In thereplication phase more NfL-positive patients according to the cutoff evolved to MS Every100-ngL increase in NfL predicted CDMS (hazard ratio [HR] 5 1009 95 CI 1005ndash1014)and McDonald MS (HR 5 1009 95 CI 1005ndash1013) remaining significant for CDMS in themultivariate analysis (adjusted HR 5 1005 95 CI 1000ndash1011) This risk was lower than thepresence of oligoclonal bands or T2 lesions

Conclusions NfL is a weak independent risk factor for MS Its role as an axonal damage biomarkermay be more relevant as suggested by its association with medium-term brain volume changesNeurologyreg 2016871076ndash1084

GLOSSARYaHR 5 adjusted hazard ratio BPF 5 brain parenchymal fraction CDMS 5 clinically definite multiple sclerosis CI 5 confi-dence interval CIS 5 clinically isolated syndrome CV 5 coefficient of variation DMT 5 disease-modifying treatmentEDSS 5 Expanded Disability Status Scale FA 5 fetuin A Gd 5 gadolinium GFAP 5 glial fibrillary acidic protein HR 5hazard ratio MS 5 multiple sclerosis NfH 5 neurofilament heavy chain NfL 5 neurofilament light chain OCB 5 oligoclonalbands PBVC 5 percentage brain volume change sema3A 5 semaphorin 3A SIENA 5 Structural Image Evaluation usingNormalization of Atrophy

Identifying patients with clinically isolated syndromes (CIS) who will present a second attackand determining the degree of disability accrual over the medium- to long-term are crucial goalsin multiple sclerosis (MS) Although MRI is the most reliable prognostic marker12 and oligo-clonal bands (OCBs) also have an important role34 the disease heterogeneity hinders a moreindividualized prognosis Therefore the search for biomarkers that capture the different aspects

These authors contributed equally to this work

DaggerThese authors contributed equally as principal investigators

From Servei de NeurologiandashNeuroimmunologia (GA CE HE JS-G ES MC JR CN CT JC AV-J IG MJA XM MT)Centre drsquoEsclerosi Muacuteltiple de Catalunya (Cemcat) Vall drsquoHebron Institut de Recerca Hospital Universitari Vall drsquoHebron Barcelona UniversitatAutogravenoma de Barcelona (GA CE HE JS-G ES MC JR CN CT JC AV-J IG XM MT) Bellaterra Departments of Neurologyand Immunology (LMV JCA-C CP) Multiple Sclerosis Unit Hospital Ramoacuten y Cajal Instituto Ramoacuten y Cajal de Investigacioacuten Sanitaria(IRYCIS) Madrid Spain Department of Neurology (JK LK) University Hospital Basel Neurocentre of Southern Switzerland (GD) OspedaleCivico Lugano Switzerland and Magnetic Resonance Unit (IDI) (DP CA AR) Hospital Universitari Vall drsquoHebron Barcelona Spain

Go to Neurologyorg for full disclosures Funding information and disclosures deemed relevant by the authors if any are provided at the end of the articleThe Article Processing Charge was paid by the authors

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

1076 copy 2016 American Academy of Neurology

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

of MS is still necessary Although many havebeen identified few are currently useful in theclinical setting5 Consequently we aimed todetermine the prognostic value of selectedbiomarkers for conversion to MS and disabil-ity accrual and to assess their associations withMRI inflammatory activity and neurodegener-ative parameters

METHODS Patients We acquired longitudinal data from

CIS cohorts at the Multiple Sclerosis Center in Vall drsquoHebron

Hospital Barcelona6 and the Neurology Department of Ramoacuten

y Cajal Hospital Madrid Inclusion criteria were age younger

than 50 years and baseline clinical evaluation within the first

3 months of disease onset We recorded baseline demographic

and clinical characteristics and conducted follow-up visits every 3

to 6 months assessing for relapses clinical worsening and

excluding patients in whom we reached alternative diagnoses A

second attack established the diagnosis of clinically definite MS

(CDMS)7 Definitions of disability accrual were a sustained

increase in the Expanded Disability Status Scale (EDSS) of 10

point over 1 year or confirmed EDSS score $30

Biological samples We collected venous blood and CSF

within 3 months of disease onset for OCB determination in

the 2 hospitals Remnant samples were aliquoted and stored at

2808C until further use

MRI acquisition and analysis At Vall drsquoHebron Hospital

brain MRI acquisition on 15- or 30-tesla superconductive

magnets included the following sequences obtained with

a contiguous 3- to 5-mm slice thickness transverse proton

density and T2-weighted conventional or fast spin-echo

transverse and sagittal T2 fluid-attenuated inversion recovery

and unenhanced and contrast-enhanced T1-weighted spin-

echo We included routine baseline spinal cord MRIs in

November 2007 Baseline scans were done within 5 months of

disease onset and follow-up MRIs at 1 year and every 5 years

thereafter6 The Ramoacuten y Cajal cohort followed a similar

acquisition protocol performing baseline and follow-up MRIs

within 3 months after the CIS and at 1 year including spinal

cord MRI in case of myelitis

Neuroradiologists scored T2 lesion number and location and

gadolinium (Gd)-enhancing and new T2 lesion number T2

lesion volume was calculated using the semiautomated Jim med-

ical image display package (Xinapse Systems Ltd Colchester

UK) Brain volume parameters were obtained using the Structural

Image Evaluation using Normalization of Atrophy (SIENA)

software part of FSL (FMRIB Software Library)8 Single-time-

point analysis to obtain brain parenchymal fraction (BPF) esti-

mates was performed with SIENAx Two-time-point analysis was

performed with SIENA estimating the percentage brain volume

change (PBVC) between 2 input images of the same subject at

different time points

Biological markers We selected fetuin A (FA)9 semaphorin

3A (sema3A)1011 glial fibrillary acidic protein (GFAP)12ndash15 neu-

rofilament heavy (NfH) and light (NfL) chains13ndash20 and neuro-

fascin2122 after a PubMed search in 2008 which we updated

regularly throughout the study duration including the terms

ldquobiological markersrdquo or ldquobiomarkersrdquo and ldquomultiple sclerosisrdquo or

ldquoclinically isolated syndromesrdquo

Except for NfH we determined biomarker levels using com-

mercial sandwich ELISA kits according to the manufacturersrsquo

recommendations (FA BioVendor Brno Czech Republic

NfL UmanDiagnostics AB Umearing Sweden GFAP Abnova

Taipei City Taiwan neurofascin USCN Life Science Inc Wuhan

China and sema3A USCN Life Science Inc) We optimized the

assays using varying sample dilutions measured in duplicates NfH

levels were determined using an electrochemiluminescence-based

solid-phase sandwich immunoassay17 at the University Hospital Basel

Switzerland selected among different assays for its higher sensitiv-

ity182324 All samples were tested blinded to clinical data and outcome

measures Whenever possible according to availability we tested sam-

ples from the same patients using a different unthawed aliquot

Experimental design Screening phaseWe selected 2 opposite

groups with a 2-year minimum follow-up from the Vall drsquoHebron

cohort CIS-CDMS (n5 from 33 to 38) including patients with 3

to 4 Barkhof-Tintore criteria on baseline MRI and presence of

OCBs who converted to CDMS and CIS-CIS (n5 from 33 to 39)

comprising patients with 0 Barkhof-Tintore criteria and absence of

OCBs who remained as CIS (figure e-1A at Neurologyorg)

Replication phaseOnly NfL levels showed significant differ-

ences in the screening and were thus evaluated in a replication

phase We selected consecutive patients with available CSF sam-

ples from the Vall drsquoHebron and Ramoacuten y Cajal cohorts (n 5

155) Patients from Vall drsquoHebron were selected from a different

time range (2009ndash2011) than the NfL screening phase because of

sample availability NfL determination was performed in each

hospital separately using the above-mentioned assay (figure e-1B)

Statistical analysis We performed parametric and nonpara-

metric descriptive statistics depending on the normality of the dis-

tributions of the continuous variables

Screening phase For each biomarker we calculated sample

size for 80 power at the 005 level of significance based on pre-

vious data We used generalized linear models to compare CIS

groups in terms of conversion to CDMS and assess biomarker levels

and disability accrual with the Bonferroni correction for multiple

comparisons when applicable Data are reported as the estimated

mean (95 confidence interval [CI]) Potential covariates were

age sex CIS topography time from CIS to lumbar puncture sam-

ple storage time and disease-modifying treatment (DMT) before

CDMS We calculated Spearman correlations for MRI inflamma-

tory activity parameters at baseline 1 and 5 years (number of T2

Gd-enhancing and new T2 lesions T2 lesion volume) and partial

correlations for neurodegenerative parameters at 1 and 5 years of

follow-up (BPF change [BPFD] adjusted for age and baseline Gd-

enhancing lesions and PBVC)We calculated BPFD by subtracting

baseline from 1- and 5-year follow-up SIENAx estimates and

dividing by the baseline values then multiplying by 100 We as-

sessed the PBVC estimated by SIENA for changes from baseline to

1 and 5 years Finally we assessed Spearman correlations between

NfL and NfH levels in a subgroup of 42 patients with determi-

nation of both biomarkers

Replication phase Primary endpoints were conversion to

CDMS and 2010 McDonald MS according to NfL status (posi-

tivenegative) based on a 900 ngL cutoff value established as the

mean 6 3 SD of NfL levels in a control group of patients with

noninflammatory neurologic diseases25 We performed uni- and

multivariate Cox proportional hazard regression analyses for NfL

levels as a continuous or dichotomic variable Covariates were

OCBs baseline T2 lesion number DMT before MS and hospital

where NfL levels were determined We used generalized linear

models to compare NfL levels in terms of disability accrual (EDSS

score $30) and Spearman correlations or generalized linear mod-

els to determine associations between NfL and MRI inflammatory

parameters at baseline and 1 year We could not assess brain volume

Neurology 87 September 13 2016 1077


changes because of the few estimated measures at the time of the

analysis

We performed statistical tests on the 005 level of signifi-

cance using the IBM SPSS Statistics (version 200 IBM Corp

Armonk NY) We also prepared figures using GraphPad Prism

502 for Windows (GraphPad Software La Jolla CA)

Standard protocol approvals registrations and patientconsents This study received approval from the corresponding

local ethical committees in both hospitals and all patients signed

a written informed consent

RESULTS Screening phase Appendix e-1A describespreliminary analyses Baseline demographic and clini-cal characteristics were comparable between CISgroups (table 1) except for the higher frequency ofoptic neuritis in CIS-CIS regarding FA NfL andNfH The proportion of patients on DMT beforeCDMS varied between 88 and 177 for eachbiomarker Mean follow-up was longer for CIS-CDMS than CIS-CIS tested for GFAP and NfHThe differences in storage time between CIS-CDMSand CIS-CIS samples for NfH did not correlate withthis biomarkerrsquos levels (rs520131 p5 0256) NfHlevels correlated with age (rs 5 0230 p5 0044) Wefound no differences in time from CIS to lumbarpuncture Therefore for each protein we adjustedthe analyses for age topography andor DMT

FA GFAP andNfH results were negative (figure e-2AndashC) We could not detect neurofascin and sema3A

As for NfL levels we found a significant differencebetween CIS-CDMS (15531 [12087ndash18975]ngL) and CIS-CIS (4990 [1688ndash8292] ngL) (p

00001) (figure 1) The average intra- and interplatecoefficients of variation (CVs) were 97 and 05respectively We found no significant differences forEDSS progression of 1 point or $30 even though inthe latter case NfL levels were 15061 (6452ndash23671)ngL in the 15 patients with EDSS score $30 and9066 (6932ndash11201) ngL if 30 (p 5 0185)We found significant correlations between NfL levelsand inflammatory activity parameters on MRI exceptfor Gd-enhancing lesions at 5 years (table 2) As forneurodegenerative parameters NfL and both BPFDand PBVC at 5 years showed the strongest correlations(table 2 figure 2)

Finally we found a correlation between NfL andNfH levels (rs 5 0466 p 5 0002)

Replication phase Appendix e-1B describes prelimi-nary analyses Baseline demographic and clinical char-acteristics are shown in table e-1 Median (interquartilerange) NfL levels were 12383 (17821) ngL for pa-tients converting to CDMS and 5558 (8255) ngLfor CIS-CIS Average intra- and interplate CV were49 and 70 at Vall drsquoHebron (n 5 93) and51 and 88 at Ramoacuten y Cajal (n 5 62)

According to the cutoff 63 patients (406) wereNfL positive Significantly more NfL-positive patients

Table 1 Demographic and clinical characteristics

FA and NfL (2010)a GFAP (2011) NfH (2012)

CIS-CDMS CIS-CIS CIS-CDMS CIS-CIS CIS-CDMS CIS-CIS

No 35 33 33 33 38 39

Mean age (SD) y 293 (73) 301 (97) 307 (80) 304 (82) 307 (75) 316 (82)

Females n () 24 (686) 26 (788) 21 (636) 24 (727) 28 (737) 32 (821)

Mean follow-up (SD)b mo 788 (334) 579 (352) 791 (362) 437 (500) 1043 (311) 743 (364)

CIS topography n ()c

Optic nerve 10 (286) 22 (667) 11 (333) 20 (606) 10 (263) 24 (615)

Brainstem 9 (257) 5 (152) 7 (212) 7 (212) 8 (211) 4 (103)

Spinal cord 11 (314) 4 (121) 10 (303) 4 (121) 14 (368) 3 (77)

Other 5 (143) 2 (61) 5 (152) 2 (61) 6 (158) 8 (205)

Mean time from CIS to lumbar puncture (SD) d 589 (535) 801 (723) 1844 (5341) 1997 (3036) 571 (525) 811 (1692)

Frozen samples mean storage time (SD)d mo 885 (341) 802 (335) 915 (345) 750 (443) 1131 (337) 976 (405)

Abbreviations CDMS 5 clinically definite multiple sclerosis CIS 5 clinically isolated syndrome FA 5 fetuin A GFAP 5 glial fibrillary acidic protein NfH 5

neurofilament heavy chain NfL 5 neurofilament light chainThe screening phase was performed between 2010 and 2012 Categorical variables x2 test Continuous variables Student t test for 2 groups analysis ofvariance for multiple comparisonsa Years in parentheses show the time when each biomarker was tested Samples were obtained between 1995 and 2008 for FA NfL and GFAP andbetween 1995 and 2009 for NfH CSF samples were aliquoted and stored at 2808C until their useb FA and NfL p 5 0050 GFAP p 5 0002 NfH p 00001c FA and NfL p 5 0017 NfH p 5 0002 GFAP p 5 0099dNfH levels p 5 0037

1078 Neurology 87 September 13 2016


converted to CDMS or fulfilled McDonald MS overtime (data not shown)

When evaluating NfL levels as a continuous vari-able in the univariate analyses we observed a 1-pointincrease in risk of both CDMS and McDonald MSfor every 100-ngL increment The adjusted hazardratio (aHR) for CDMS remained significant in themultivariate analysis (table 3)

As for NfL status NfL positivity was a predictor ofCDMS (HR 2279 95 CI 1283ndash4049 p5 0005)andMcDonaldMS (HR 2801 95CI 1761ndash4455p 00001) in the univariate analyses however thissignificance was lost in the multivariate models (aHR1220 95 CI 0656ndash2269 p 5 0530 and aHR1347 95 CI 0809ndash2244 p5 0252 respectively)

Regarding disability although NfL levels were26356 (12264ndash40448) ngL in the 11 patientswith EDSS score $30 and 15605 (9348ndash21862)ngL if 30 this difference was not statistically sig-nificant (p 5 0172)

Finally we found significant correlations betweenNfL levels and T2 lesion volume and Gd-enhancinglesion number on baseline MRIs (n 5 63 rs 5 0517

p 00001 and n 5 146 rs 5 0469 p 00001respectively) and follow-up MRIs (n 5 36 rs 5 0420p5 0011 for new T2 lesion volume and n5 94 rs 50231 p 5 0025 for Gd-enhancing lesions) HigherNfL levels were associated with a higher T2 lesion num-ber at baseline and 1 year (data not shown)

DISCUSSION In the screening phase we aimed toidentify differences in biomarker levels under therationale that if none were found between 2 oppositeCIS groups26 none would be found in consecutivepatients a scenario that better resembles clinical prac-tice In addition this phase allows a strict use ofbiological samples Only NfL levels were significantlyhigher in patients who converted to MS compared tononconverters Neurofilaments are type IV interme-diate filaments specific for neurons released into theCSF when axonal damage occurs162728 A study with38 patients reported higher NfL levels in CIS-CDMScompared to CIS-CIS18 a finding unconfirmed in otherinvestigations including 9 to 36 patients per group202930

Such discrepancies could be attributable to a smallsample size in the converter group2030 homogeneity inbaseline inflammatory parameters such as proportion ofOCBs present in both CIS groups29 or the method usedto detect NfL30 In addition sample size calculations arenot referred and some groups may be too small toproperly demonstrate any differences Our study wasadequately powered and thus confirms the differenceswith a well-balanced distribution between groups

We found no associations between NfL levels anddisability by the EDSS Except for one most studiesshowed significant correlations but the analysesincluded CIS and other MS phenotypes observing thestrongest correlations in progressive forms13141831ndash33

Khalil et al20 evaluated 67 patients with CIS exclusivelyand found a marginal correlation coefficient of rs 50324 (p 005) When assessing NfL levels accordingto EDSS score$30 in both phases they were higher inpatients with more severe disability but the differencewas not significant a finding probably influenced by thefew patients who reached such EDSS score

Table 2 Correlations between baseline neurofilament light chain levels and MRI measures at baseline 1 year and 5 years Screening phase

Baseline Year 1 Year 5

T2LN T2LV Gd1 T2LN T2LV T2New Gd1 BPFD PBVC T2LN T2LV T2New Gd1 BPFD PBVC

Noa 39 39 39 38 38 40 38 33 30 21 21 23 22 21 18

rb 0595 0617 0538 0619 0649 0492 0456 20558 20345 0570 0609 0589 0167 20892 20842

p Value 00001 00001 00001 00001 00001 0001 0004 0001 0072 0007 0003 0003 0456 00001 00001

Abbreviations BPFD 5 brain parenchymal fraction percentage change Gd1 5 number of gadolinium-enhancing lesions PBVC 5 percentage brain volumechange T2LN 5 T2 lesion number T2LV 5 T2 lesion volume T2New 5 number of new T2 lesionsaData assessed in MRI scans performed from 2001bMRI inflammatory measures assessed with Spearman correlation BPFD and PBVC values correspond to partial correlations adjusted for age and Gd1lesions at baseline

Figure 1 NfL levels in the 2 CIS groups

Results adjusted for CIS topography and disease-modifying treatment CDMS 5 clinicallydefinite multiple sclerosis CIS 5 clinically isolated syndrome NfL 5 neurofilament lightchain



We observed significant associations between NfLand MRI inflammatory parameters on baseline andfollow-up MRIs with similar findings during the rep-lication phase Regarding Gd-enhancing lesions in thescreening we found correlations with NfL levels atbaseline and 1 year observed again in the replicationphase but not at 5 years There are previous reportsof correlations with T2 lesion number and Gd-enhancing lesions in CIS andor MS groups1825

unconfirmed in other CIS-specific studies2034 Themost striking findings concern MRI neurodegenerativeparameters our results suggest baseline NfL levelsincrease not only in association with lesion loadaccrual and activity but also independently of theseparameters3536 On the contrary a previous study did

not find any correlations between NfL levels and brainvolume change in CIS20 Although the authors didadjust for age and used the SIENA software they as-sessed the follow-up only at 1 year and did not controlby Gd-enhancing lesions We additionally evaluatedthe association between baseline NfL levels and brainvolume changes at 5 years Our findings are partlysupported by those of Burman et al15 in which NfLlevels were elevated irrespective of Gd-enhancing le-sions in progressive MS Unfortunately our appraisalis limited our sample size was small and we wereunable to repeat this evaluation in the replicationphase However by estimating both BPFD and PBVCthe latter a robust method we believe our results arereliable and should be assessed in future studies

Figure 2 Scatterplots showing the correlations between NfL levels and brain volume changes

The graphs represent the raw data The correlation coefficients and p values correspond to the partial correlations adjusted for age and baseline gadolinium-enhancing lesions (A) BPF change at 1 year (B) PBVC at 1 year (C) BPF change at 5 years (D) PBVC at 5 years BPF 5 brain parenchymal fractionNfL 5 neurofilament light chain PBVC 5 percentage brain volume change



Of note there was a significant correlationbetween NfL and NfH levels in accordance with pre-vious publications on CIS and relapsing-remittingMS182031 although contrary to our results some ofthese studies demonstrated associations between NfHand EDSS or MRI parameters1820 Thus the origin ofthis correlation in our study is a matter of debate anddeserves further study

In the replication phase considering that a dichoto-mic biomarker could be more useful in the clinicalpractice we explored a 900 ngL cutoff25 observingthat more NfL-positive than -negative patients evolved

to CDMS and McDonald MS Two other studiesexplored cutoff values to either identify relapses or pre-dict evolution to secondary progressive MS1337 Theircutoff values however are lower than ours a findingpossibly related not only to the different outcomes butalso to the use of a different assay13 or the calculationmethods based on NfL levels in patients with MS1337

whereas we established our cutoff using a control groupwith noninflammatory neurologic diseases under therationale that this value would be more stable acrossstudies To assess whether this is a better approach thecutoff should be evaluated in other cohorts One studyexplored NfL levels and fulfillment of the 2010 dis-semination in space criteria in optic neuritis34 whereaswe used the cutoff value to investigate the risk of devel-oping both CDMS and 2010 McDonald MS at thetime of a CIS Another contribution is the assessmentof NfL as an independent risk factor for MS In theunivariate analyses we found a higher risk of CDMSandMcDonaldMS for every 100-ngL increase in NfLlevels maintained for CDMS in the multivariate anal-ysis The nonsignificant results for McDonald MScould be conditioned by the distribution of patientsover the different categories in the multivariate analy-sis the correlations between NfL levels and T2 lesionsand the strong predictive value of T2 lesions for dis-semination in space fulfillment When assessing NfLstatus the increased risk of both CDMS and McDo-nald MS in the univariate analyses was lost in themultivariate models Thus although NfL status couldbe more practical in the clinical setting in our studyonly NfL as a continuous variable is an independentrisk factor for CDMS Nevertheless the value of NfLshould be considered in context with OCB and T2lesion results and according to a recent study it couldbe considered a weak risk factor for MS6

Despite conducting measures to minimize biasa limitation in the replication phase concerns theNfL determination in 2 different centers Althoughthe corresponding intra- and interplate CVs werewithin the assayrsquos standardized limits we did not per-form quality controls such as testing the same samplesin both centers38 Besides the shorter follow-up of theVall drsquoHebron cohort in the replication phase maypreclude excluding patients with potential alternativediagnoses nevertheless the specific inclusion of typicalCIS presentations lowers this risk6 Furthermorea shortcoming of NfL levels is their determination inCSF because some centers do not perform lumbarpunctures routinely It is impossible to quantify serumNfL levels with the available ELISA2930 howevera new electrochemiluminescence array showed prom-ising results in detecting higher serum NfL levels inpatients with CIS compared to healthy controls39

Our biomarker list was probably not thoroughlycomprehensive We did however search for updates

Table 3 Uni- and multivariate analyses for CDMS and 2010 McDonald MS withNfL as a continuous variable

p Value HRaHRa 95 CI

Conversion to CDMS

Univariate analysis

DMTb 0701 1126 0615ndash2062

Hospital 0063 1722 0971ndash3052

NfL-100c 00001 1009 1005ndash1014

OCBs 00001 6074 2580ndash14300

T2 lesions 1ndash3 0047 8537 1026ndash71004

T2 lesions Dagger4 0002 21709 2982ndash158026

Multivariate analysisd

NfL-100 0040 1005 1000ndash1011

OCBs 0048 2597 1009ndash6683



2010 McDonald criteria

Univariate analysis

DMT 0292 0736 0416ndash1302

NfL-100 00001 1009 1005ndash1013

Hospitale 0001 2232 1404ndash3546

OCBs 00001 8427 4189ndash16951



Multivariate analysisf

NfL-100 0155 1004 0999ndash1008

OCBs 0012 2669 1236ndash5762



Abbreviations aHR 5 adjusted hazard ratio CDMS 5 clinically definite multiple sclerosisCI 5 confidence interval DMT 5 disease-modifying treatment HR 5 hazard ratioNfL 5 neurofilament light chain OCB 5 oligoclonal bandsaUnivariate analyses HR multivariate analyses aHRbDMT before conversion to CDMS or fulfillment of the 2010 McDonald criteriac HR increase for every 100 ngLdResults were not modified before and after adjusting for DMTeHigher risk of McDonald MS for cases from Ramoacuten y Cajal Hospitalf Results adjusted for hospital and DMT When only adjusting for hospital aHR for NfLremained similar (aHR 1004 95 CI 0999ndash1009) but with a p value of 0081



throughout the study duration Besides the proper-ties of the selected assays could have influenced ourfindings Another limitation is the difficulty in assess-ing all biomarkers in the same patients without com-promising the sample size given the limited CSFaliquot availability Nevertheless the homogeneousdata collection and systematic sample storage proce-dures could aid to minimize bias Finally we didnot compare the NfH electrochemiluminescenceassay to other methods

Therefore elevated NfL levels indicate a higher riskof evolving to MS However the increase in risk forevery 100 ngL could be difficult to interpret in thedaily clinical practice and compared to OCBs andT2 lesions NfL levels are a weak risk factor for MSThe search for a cutoff value should be assessed inother cohorts and finally the value of NfL as a markerof axonal damage may be more relevant as suggested bythe correlations with medium-term brain volume loss

AUTHOR CONTRIBUTIONSGeorgina Arrambide participated in the design of the work and on the

acquisition statistical analysis and interpretation of data for the work

drafted and revised it approved the present version to be published

and agreed to be accountable for all aspects of the work Carmen Espejo

participated in the design of the work and on the analysis and interpre-

tation of data for the work drafted and revised it for important intellec-

tual content approved the present version to be published and agreed to

be accountable for all aspects of the work Herena Eixarch participated in

the analysis and interpretation of data for the work drafted and revised it

for important intellectual content approved the present version to be

published and agreed to be accountable for all aspects of the work Luisa

M Villar participated in the acquisition analysis and interpretation of

data for the work revised it for important intellectual content approved

the present version to be published and agreed to be accountable for all

aspects of the work Joseacute C Alvarez-Cermentildeo participated in the acqui-

sition analysis and interpretation of data for the work revised it for

important intellectual content approved the present version to be pub-

lished and agreed to be accountable for all aspects of the work Carmen

Picoacuten participated in the acquisition and analysis of data for the work

revised it for important intellectual content approved the present version

to be published and agreed to be accountable for all aspects of the work

Jens Kuhle participated in the acquisition analysis and interpretation of



aspects of the work Giulio Disanto participated in the acquisition and

analysis of data for the work revised it for important intellectual content

approved the present version to be published and agreed to be account-

able for all aspects of the work Ludwig Kappos participated in the

analysis and interpretation of data for the work revised it for important

intellectual content approved the present version to be published and

agreed to be accountable for all aspects of the work Jaume Sastre-Garriga

participated in the design and acquisition analysis and interpretation of



aspects of the work Deborah Pareto participated in the acquisition



agreed to be accountable for all aspects of the work Eva Simon partic-

ipated in the acquisition of data for the work revised it for important


agreed to be accountable for all aspects of the work Manuel Comabella

participated in the acquisition and interpretation of data for the work



Jordi Riacuteo participated in the acquisition and interpretation of data for the

work revised it for important intellectual content approved the present

version to be published and agreed to be accountable for all aspects of

the work Carlos Nos participated in the interpretation of data for the



the work Carmen Tur participated in the acquisition and interpretation

of data for the work revised it for important intellectual content


able for all aspects of the work Joaquiacuten Castilloacute participated in the

acquisition and interpretation of data for the work revised it for impor-

tant intellectual content approved the present version to be published

and agreed to be accountable for all aspects of the work Angela Vidal-

Jordana participated in the acquisition and interpretation of data for the



the work Ingrid Galaacuten participated in the acquisition and interpretation



able for all aspects of the work Maria J Areacutevalo participated in the

acquisition of data for the work revised it for important intellectual

content approved the present version to be published and agreed to

be accountable for all aspects of the work Cristina Auger participated

in the analysis and interpretation of data for the work revised it for


lished and agreed to be accountable for all aspects of the work Alex

Rovira participated in the analysis and interpretation of data for the work

revised it for important intellectual content approved the present version to

be published and agreed to be accountable for all aspects of the work

Xavier Montalban participated in the conception and design of the

work and on the acquisition analysis and interpretation of data for the


version to be published and agreed to be accountable for all aspects of the

work Mar Tintore participated in the conception and design of the work

and on the acquisition analysis and interpretation of data for the work



ACKNOWLEDGMENTThe authors thank Xavier Vidal for statistical analysis support (Depart-

ment of Pharmacology Vall drsquoHebron University Hospital Barcelona

Spain) the Red Espantildeola de Esclerosis Muacuteltiple (REEM) (RD070060

RD120032) sponsored by the Fondo de Investigacioacuten Sanitaria (FIS) the

Instituto de Salud Carlos III the Ministry of Economy and Competitive-

ness in Spain and the Ajuts per donar Suport als Grups de Recerca de

Catalunya (2009 SGR 0793 2014 SGR 1082) sponsored by the Agegravencia

de Gestioacute drsquoAjuts Universitaris i de Recerca (AGAUR) of the Generalitat

de Catalunya in Spain

STUDY FUNDINGThis project was supported by FIS PI080788 and PI1201313 from the

FIS of the Ministry of Economy and Competitiveness of Spain and by

a McDonald Fellowship awarded to Georgina Arrambide by the MSIF

Carmen Espejo is partially supported by the Miguel Servet program

(CP0700146 CP1300028) Herena Eixarch is supported by the Sara

Borrell program (CD090363) and Angela Vidal-Jordana received sup-

port for research training contracts Rio Hortega (CM1000032) all from

the FIS Instituto de Salud Carlos III Ministry of Economy and Compet-

itiveness of Spain Jens Kuhle was supported by an ECTRIMS Research

Fellowship Programme and by the Forschungsfonds of the University of

Basel Switzerland

DISCLOSUREG Arrambide has received compensation for consulting services from

Biogen Idec and research support from Novartis C Espejo and H Eix-

arch report no disclosures relevant to the manuscript L Villar has

received speaking honoraria or research support from Bayer Schering

Pharma Merck Serono Biogen Idec Teva Pharmaceuticals Sanofi-

Aventis Genzyme and Novartis J Alvarez-Cermentildeo has received com-

pensation for consulting services and speaking honoraria from Bayer

Schering Pharma Merck Serono Biogen Idec Teva Pharmaceuticals



Sanofi-Aventis and Novartis C Picoacuten reports no disclosures relevant to

the manuscript J Kuhle has received research support from the Swiss MS

Society Swiss ALS Society Protagen AG Roche Genzyme and Novartis

and served on scientific advisory boards for GenzymeSanofi-Aventis

Merck Serono and Novartis Pharma G Disanto reports no disclosures

relevant to the manuscript L Kappos has received and dedicated to

research support fees for board membership consultancy or speaking

or grants in the last 3 years from Actelion Advancells Allozyne Bayer

Bayhill Biogen Idec BioMarin CSL Behring Eli Lilly European Union

GeNeuro Genmab Gianni Rubatto Foundation Glenmark Merck

Serono MediciNova Mitsubishi Pharma Novartis Novartis Research

Foundation Novo Nordisk Peptimmune Roche Roche Research Foun-

dation Sanofi-Aventis Santhera Swiss MS Society Swiss National

Research Foundation Teva UCB and Wyeth J Sastre-Garriga has

received compensation for participating on advisory boards speaking

honoraria and travel expenses for scientific meetings consulting services

or research support from Novartis Biogen Idec Sanofi-Aventis Teva

Serono Symposia International Foundation Merck Serono Almirall and

Genzyme D Pareto and E Simon report no disclosures relevant to the

manuscript M Comabella has received compensation for consulting

services and speaking honoraria from Bayer Schering Pharma Merck

Serono Biogen Idec Teva Pharmaceuticals Sanofi-Aventis and Novar-

tis J Riacuteo has received speaking honoraria and personal compensation for

participating on advisory boards from Almirall Bayer Schering Health-

care Biogen Idec Genzyme Merck Serono Novartis Teva and Sanofi-

Aventis C Nos C Tur J Castilloacute A Vidal-Jordana I Galaacuten

M Areacutevalo and C Auger report no disclosures relevant to the manu-

script A Rovira serves on scientific advisory boards for Neuro-Tec and

on the editorial board of the American Journal of Neuroradiology and

Neuroradiology has received speaker honoraria from Bayer Schering Phar-

ma Sanofi-Aventis Bracco Merck Serono Teva Pharmaceutical Indus-

tries Ltd and Biogen Idec receives research support from Bayer Schering

Pharma and serves as a consultant for Novartis X Montalban has

received speaking honoraria and travel expenses for scientific meetings

has been a steering committee member of clinical trials or participated in

advisory boards of clinical trials in the past with Almirall Bayer Biogen

Genzyme Merck Novartis Receptos Roche Sanofi Genzyme and Teva

Pharmaceuticals M Tintore has received compensation for consulting


Serono Biogen Idec Teva Pharmaceuticals Sanofi-Aventis Novartis

Almirall Genzyme and Roche Go to Neurologyorg for full disclosures

Received August 3 2015 Accepted in final form April 14 2016

REFERENCES1 Fisniku LK Brex PA Altmann DR et al Disability and T2

MRI lesions a 20-year follow-up of patients with relapse

onset of multiple sclerosis Brain 2008131808ndash817

2 Polman CH Reingold SC Banwell B et al Diagnostic cri-

teria for multiple sclerosis 2010 revisions to the McDonald

criteria Ann Neurol 201169292ndash302

3 Tintore M Rovira A Rio J et al Do oligoclonal bands

add information to MRI in first attacks of multiple scle-

rosis Neurology 2008701079ndash1083

4 Masjuan J Alvarez-Cermeno JC Garcia-Barragan N et al

Clinically isolated syndromes a new oligoclonal band test

accurately predicts conversion to MS Neurology 200666

576ndash578

5 Comabella M Montalban X Body fluid biomarkers in

multiple sclerosis Lancet Neurol 201413113ndash126

6 Tintore M Rovira A Rio J et al Defining high medium

and low impact prognostic factors for developing multiple

sclerosis Brain 20151381863ndash1874

7 Poser CM Paty DW Scheinberg L et al New diagnostic

criteria for multiple sclerosis guidelines for research pro-

tocols Ann Neurol 198313227ndash231

8 Smith SM Jenkinson M Woolrich MW et al Advances

in functional and structural MR image analysis and

implementation as FSL Neuroimage 200423(suppl 1)

S208ndashS219

9 Tumani H Lehmensiek V Rau D et al CSF proteome

analysis in clinically isolated syndrome (CIS) candidate

markers for conversion to definite multiple sclerosis Neu-

rosci Lett 2009452214ndash217

10 Williams A Piaton G Aigrot MS et al Semaphorin 3A

and 3F key players in myelin repair in multiple sclerosis

Brain 20071302554ndash2565

11 Eixarch H Gutierrez-Franco A Montalban X Espejo C

Semaphorins 3A and 7A potential immune and neuro-

regenerative targets in multiple sclerosis Trends Mol Med

201319157ndash164

12 Petzold A Eikelenboom MJ Gveric D et al Markers for

different glial cell responses in multiple sclerosis clinical and

pathological correlations Brain 20021251462ndash1473

13 Malmestrom C Haghighi S Rosengren L Andersen O

Lycke J Neurofilament light protein and glial fibrillary

acidic protein as biological markers in MS Neurology

2003611720ndash1725

14 Norgren N Sundstrom P Svenningsson A Rosengren L

Stigbrand T Gunnarsson M Neurofilament and glial

fibrillary acidic protein in multiple sclerosis Neurology

2004631586ndash1590

15 Burman J Zetterberg H Fransson M Loskog AS

Raininko R Fagius J Assessing tissue damage in multiple

sclerosis a biomarker approach Acta Neurol Scand 2014

13081ndash89

16 Petzold A Neurofilament phosphoforms surrogate markers

for axonal injury degeneration and loss J Neurol Sci 2005

233183ndash198

17 Kuhle J Regeniter A Leppert D et al A highly sensitive

electrochemiluminescence immunoassay for the neurofilament

heavy chain protein J Neuroimmunol 2010220114ndash119

18 Teunissen CE Iacobaeus E Khademi M et al Combina-

tion of CSF N-acetylaspartate and neurofilaments in mul-

tiple sclerosis Neurology 2009721322ndash1329

19 Kuhle J Leppert D Petzold A et al Neurofilament heavy

chain in CSF correlates with relapses and disability in

multiple sclerosis Neurology 2011761206ndash1213

20 Khalil M Enzinger C Langkammer C et al CSF neuro-

filament and N-acetylaspartate related brain changes in clin-

ically isolated syndrome Mult Scler 201319436ndash442

21 Mathey EK Derfuss T Storch MK et al Neurofascin as

a novel target for autoantibody-mediated axonal injury

J Exp Med 20072042363ndash2372

22 Kawamura N Yamasaki R Yonekawa T et al Anti-neuro-

fascin antibody in patients with combined central and

peripheral demyelination Neurology 201381714ndash722

23 Shaw G Yang C Ellis R et al Hyperphosphorylated neuro-

filament NF-H is a serum biomarker of axonal injury

Biochem Biophys Res Commun 20053361268ndash1277

24 Petzold A Keir G Green AJ Giovannoni G Thompson EJ

A specific ELISA for measuring neurofilament heavy chain

phosphoforms J Immunol Methods 2003278179ndash190

25 Villar LM Picon C Costa-Frossard L et al Cerebrospinal

fluid immunological biomarkers associated with axonal dam-

age in multiple sclerosis Eur J Neurol 2015221169ndash1175

26 Comabella M Fernandez M Martin R et al Cerebrospi-

nal fluid chitinase 3-like 1 levels are associated with con-

version to multiple sclerosis Brain 20101331082ndash1093

27 Nylen K Csajbok LZ Ost M et al CSFndashneurofilament

correlates with outcome after aneurysmal subarachnoid

hemorrhage Neurosci Lett 2006404132ndash136



28 Petzold A Keir G Warren J Fox N Rossor MN A

systematic review and meta-analysis of CSF neurofilament

protein levels as biomarkers in dementia Neurodegener

Dis 20074185ndash194

29 Fialova L Bartos A Svarcova J Zimova D Kotoucova J

Malbohan I Serum and cerebrospinal fluid light neuro-

filaments and antibodies against them in clinically isolated

syndrome and multiple sclerosis J Neuroimmunol 2013

262113ndash120

30 Avsar T Korkmaz D Tutuncu M et al Protein biomarkers

for multiple sclerosis semi-quantitative analysis of cerebro-

spinal fluid candidate protein biomarkers in different forms

of multiple sclerosis Mult Scler 2012181081ndash1091

31 Kuhle J Plattner K Bestwick JP et al A comparative

study of CSF neurofilament light and heavy chain protein

in MS Mult Scler 2013191597ndash1603

32 Semra YK Seidi OA Sharief MK Heightened intrathecal

release of axonal cytoskeletal proteins in multiple sclerosis

is associated with progressive disease and clinical disability

J Neuroimmunol 2002122132ndash139

33 Trentini A Comabella M Tintore M et al N-acetylaspartate

and neurofilaments as biomarkers of axonal damage in pa-

tients with progressive forms of multiple sclerosis

J Neurol 20142612338ndash2343

34 Modvig S Degn M Horwitz H et al Relationship

between cerebrospinal fluid biomarkers for inflammation

demyelination and neurodegeneration in acute optic neu-

ritis PLoS One 20138e77163

35 Perez-Miralles F Sastre-Garriga J Tintore M et al Clin-

ical impact of early brain atrophy in clinically isolated

syndromes Mult Scler 2013191878ndash1886

36 Bielekova B McDermott MP Will CSF biomarkers guide

future therapeutic decisions in multiple sclerosis

Neurology 2015841620ndash1621

37 Salzer J Svenningsson A Sundstrom P Neurofilament light

as a prognostic marker in multiple sclerosis Mult Scler

201016287ndash292

38 Petzold A Altintas A Andreoni L et al Neurofila-

ment ELISA validation J Immunol Methods 2010

35223ndash31

39 Disanto G Adiutori R Dobson R et al Serum neurofila-

ment light chain levels are increased in patients with a clin-

ically isolated syndrome J Neurol Neurosurg Psychiatry

201687126ndash129

Carry the Only Card that Helps Support the AANmdashandGet a $100 Cash Rewards Bonus

Apply for the BankAmericard Cash RewardsTM credit card today to start getting more cash back forthe things you buy mostmdashplus a $100 cash rewards bonus offer Visit AANcomviewCashRewardsand enter priority code ldquoVACN51rdquo

Discover AltmetricsSee real-time downloads and online activity for articles

Authors and readers alike can view real-time data on articles including downloads and online activityacross multiple sources Click on the ldquoArticle Metricsrdquo link in the right column of an article for detailsTo learn more about article metrics visit httpwwwneurologyorgsitemiscarticle_usagexhtml



DOI 101212WNL00000000000030852016871076-1084 Published Online before print August 12 2016Neurology

Georgina Arrambide Carmen Espejo Herena Eixarch et al Neurofilament light chain level is a weak risk factor for the development of MS

This information is current as of August 12 2016

rights reserved Print ISSN 0028-3878 Online ISSN 1526-632X1951 it is now a weekly with 48 issues per year Copyright copy 2016 American Academy of Neurology All

reg is the official journal of the American Academy of Neurology Published continuously sinceNeurology

ServicesUpdated Information amp

httpnneurologyorgcontent87111076fullincluding high resolution figures can be found at

Supplementary Material

085DC2httpnneurologyorgcontentsuppl20160814WNL0000000000003

085DC1httpnneurologyorgcontentsuppl20160814WNL0000000000003Supplementary material can be found at

References httpnneurologyorgcontent87111076fullref-list-1

This article cites 39 articles 10 of which you can access for free at

Citations httpnneurologyorgcontent87111076fullotherarticles

This article has been cited by 4 HighWire-hosted articles

Subspecialty Collections

httpnneurologyorgcgicollectionvolumetric_mriVolumetric MRI

httpnneurologyorgcgicollectionprognosisPrognosis

httpnneurologyorgcgicollectionmultiple_sclerosisMultiple sclerosis

httpnneurologyorgcgicollectionautoimmune_diseasesAutoimmune diseasesfollowing collection(s) This article along with others on similar topics appears in the

Errata

content871920681fullpdf or page

nextAn erratum has been published regarding this article Please see

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httpwwwneurologyorgaboutabout_the_journalpermissionsits entirety can be found online atInformation about reproducing this article in parts (figurestables) or in

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generates the question Would this high exacerbationrate happen if patients were allowed to achieve remis-sion with steroids without using MMF

It was previously illustrated that among patientswith MG who were treated with steroids 802(93116) achieved remissionminimal manifestationsstatus and only 18 (1793) experienced an exacer-bation afterward2 This clues in that the high exacer-bation rate reported by Oskarsson et al afterdiscontinuing MMF may not reflect the natural dis-ease activity but rather reflects MMF dependenceand that continuing MMF mainly treats the depen-dence Both studies are limited by a lack of informa-tion on the prednisone dose required to maintainremissionminimal manifestations status (an impor-tant data point to determine whether MMF iseffective)

Author Response Bjoumlrn Oskarsson SacramentoDavidM Rocke Davis KarstenDengel SacramentoDavid P Richman Davis CA We thank Dimachkieet al for their interest in our article1 However in oppo-sition to Dimachkie et al we would consider MGexacerbations after discontinuation of MMF as MGexacerbations rather than a novel MMF dependence

condition Given this premise patients with pharmaco-logically controlled MG seem a more appropriate con-trol group compared to patients who had MG butsustain remission without pharmacologic treatmentWe would suspect that patients without symptomsor treatment may have a less-active disease comparedto a population requiring treatment This last group isalso rare in our clinic further making such a compari-son less meaningful

The patients were selected on the basis of being onstable doses of prednisone (0ndash25 mgd see table 2)1

and only MMF was varied Our article does notaddress corticosteroid treatment of MG and we donot argue that corticosteroids are not an effectivetreatment of MG The interest in treating MG withMMF stems primarily from MMFrsquos more favorableside-effect profile

copy 2016 American Academy of Neurology

1 Oskarsson B Rocke DM Dengel K Richman DP Myas-

thenia gravis exacerbation after discontinuing mycopheno-

late a single-center cohort study Neurology 201686

1159ndash1163

2 Pascuzzi RM Coslett HB Johns TR Long-term cortico-

steroid treatment of myasthenia gravis report of 116 pa-

tients Ann Neurol 198415291ndash298

CORRECTIONSNeurofilament light chain level is a weak risk factor for the development of MS

In the article ldquoNeurofilament light chain level is a weak risk factor for the development of MSrdquo by G Arrambide et al1

there is an error in figure 2 In panel C the p value should read ldquop 00001rdquo rather than ldquop 00001rdquo as originallypublished The editorial staff regrets the error

REFERENCE1 Arrambide G Espejo C Eixarch H et al Neurofilament light chain level is a weak risk factor for the development of

MS Neurology 2016871076ndash1084

Pediatric multiple sclerosis Conventional first-line treatment and general management

In the article ldquoPediatric multiple sclerosis Conventional first-line treatment and general managementrdquo by A Ghezzi et al1

there is an error in the fourth authorrsquos name which should have read ldquoTeri Schreinerrdquo rather than ldquoTeri Shreinerrdquo asoriginally published The authors regret the error

REFERENCE1 Ghezzi A Amato MP Makhani N et al Pediatric multiple sclerosis conventional first-line treatment and general

management Neurology 201687(suppl 2)S97ndashS102

Author disclosures are available upon request (journalneurologyorg)

2068 Neurology 87 November 8 2016


of MS is still necessary Although many havebeen identified few are currently useful in theclinical setting5 Consequently we aimed todetermine the prognostic value of selectedbiomarkers for conversion to MS and disabil-ity accrual and to assess their associations withMRI inflammatory activity and neurodegener-ative parameters

METHODS Patients We acquired longitudinal data from

CIS cohorts at the Multiple Sclerosis Center in Vall drsquoHebron

Hospital Barcelona6 and the Neurology Department of Ramoacuten

y Cajal Hospital Madrid Inclusion criteria were age younger

than 50 years and baseline clinical evaluation within the first

3 months of disease onset We recorded baseline demographic

and clinical characteristics and conducted follow-up visits every 3

to 6 months assessing for relapses clinical worsening and

excluding patients in whom we reached alternative diagnoses A

second attack established the diagnosis of clinically definite MS

(CDMS)7 Definitions of disability accrual were a sustained

increase in the Expanded Disability Status Scale (EDSS) of 10

point over 1 year or confirmed EDSS score $30

Biological samples We collected venous blood and CSF

within 3 months of disease onset for OCB determination in

the 2 hospitals Remnant samples were aliquoted and stored at

2808C until further use

MRI acquisition and analysis At Vall drsquoHebron Hospital

brain MRI acquisition on 15- or 30-tesla superconductive

magnets included the following sequences obtained with

a contiguous 3- to 5-mm slice thickness transverse proton

density and T2-weighted conventional or fast spin-echo

transverse and sagittal T2 fluid-attenuated inversion recovery

and unenhanced and contrast-enhanced T1-weighted spin-

echo We included routine baseline spinal cord MRIs in

November 2007 Baseline scans were done within 5 months of

disease onset and follow-up MRIs at 1 year and every 5 years

thereafter6 The Ramoacuten y Cajal cohort followed a similar

acquisition protocol performing baseline and follow-up MRIs

within 3 months after the CIS and at 1 year including spinal

cord MRI in case of myelitis

Neuroradiologists scored T2 lesion number and location and

gadolinium (Gd)-enhancing and new T2 lesion number T2

lesion volume was calculated using the semiautomated Jim med-

ical image display package (Xinapse Systems Ltd Colchester

UK) Brain volume parameters were obtained using the Structural

Image Evaluation using Normalization of Atrophy (SIENA)

software part of FSL (FMRIB Software Library)8 Single-time-

point analysis to obtain brain parenchymal fraction (BPF) esti-

mates was performed with SIENAx Two-time-point analysis was

performed with SIENA estimating the percentage brain volume

change (PBVC) between 2 input images of the same subject at

different time points

Biological markers We selected fetuin A (FA)9 semaphorin

3A (sema3A)1011 glial fibrillary acidic protein (GFAP)12ndash15 neu-

rofilament heavy (NfH) and light (NfL) chains13ndash20 and neuro-

fascin2122 after a PubMed search in 2008 which we updated

regularly throughout the study duration including the terms

ldquobiological markersrdquo or ldquobiomarkersrdquo and ldquomultiple sclerosisrdquo or

ldquoclinically isolated syndromesrdquo

Except for NfH we determined biomarker levels using com-

mercial sandwich ELISA kits according to the manufacturersrsquo

recommendations (FA BioVendor Brno Czech Republic

NfL UmanDiagnostics AB Umearing Sweden GFAP Abnova

Taipei City Taiwan neurofascin USCN Life Science Inc Wuhan

China and sema3A USCN Life Science Inc) We optimized the

assays using varying sample dilutions measured in duplicates NfH

levels were determined using an electrochemiluminescence-based

solid-phase sandwich immunoassay17 at the University Hospital Basel

Switzerland selected among different assays for its higher sensitiv-

ity182324 All samples were tested blinded to clinical data and outcome

measures Whenever possible according to availability we tested sam-

ples from the same patients using a different unthawed aliquot

Experimental design Screening phaseWe selected 2 opposite

groups with a 2-year minimum follow-up from the Vall drsquoHebron

cohort CIS-CDMS (n5 from 33 to 38) including patients with 3

to 4 Barkhof-Tintore criteria on baseline MRI and presence of

OCBs who converted to CDMS and CIS-CIS (n5 from 33 to 39)

comprising patients with 0 Barkhof-Tintore criteria and absence of

OCBs who remained as CIS (figure e-1A at Neurologyorg)

Replication phaseOnly NfL levels showed significant differ-

ences in the screening and were thus evaluated in a replication

phase We selected consecutive patients with available CSF sam-

ples from the Vall drsquoHebron and Ramoacuten y Cajal cohorts (n 5

155) Patients from Vall drsquoHebron were selected from a different

time range (2009ndash2011) than the NfL screening phase because of

sample availability NfL determination was performed in each

hospital separately using the above-mentioned assay (figure e-1B)

Statistical analysis We performed parametric and nonpara-

metric descriptive statistics depending on the normality of the dis-

tributions of the continuous variables

Screening phase For each biomarker we calculated sample

size for 80 power at the 005 level of significance based on pre-

vious data We used generalized linear models to compare CIS

groups in terms of conversion to CDMS and assess biomarker levels

and disability accrual with the Bonferroni correction for multiple

comparisons when applicable Data are reported as the estimated

mean (95 confidence interval [CI]) Potential covariates were

age sex CIS topography time from CIS to lumbar puncture sam-

ple storage time and disease-modifying treatment (DMT) before

CDMS We calculated Spearman correlations for MRI inflamma-

tory activity parameters at baseline 1 and 5 years (number of T2

Gd-enhancing and new T2 lesions T2 lesion volume) and partial

correlations for neurodegenerative parameters at 1 and 5 years of

follow-up (BPF change [BPFD] adjusted for age and baseline Gd-

enhancing lesions and PBVC)We calculated BPFD by subtracting

baseline from 1- and 5-year follow-up SIENAx estimates and

dividing by the baseline values then multiplying by 100 We as-

sessed the PBVC estimated by SIENA for changes from baseline to

1 and 5 years Finally we assessed Spearman correlations between

NfL and NfH levels in a subgroup of 42 patients with determi-

nation of both biomarkers

Replication phase Primary endpoints were conversion to

CDMS and 2010 McDonald MS according to NfL status (posi-

tivenegative) based on a 900 ngL cutoff value established as the

mean 6 3 SD of NfL levels in a control group of patients with

noninflammatory neurologic diseases25 We performed uni- and

multivariate Cox proportional hazard regression analyses for NfL

levels as a continuous or dichotomic variable Covariates were

OCBs baseline T2 lesion number DMT before MS and hospital

where NfL levels were determined We used generalized linear

models to compare NfL levels in terms of disability accrual (EDSS

score $30) and Spearman correlations or generalized linear mod-

els to determine associations between NfL and MRI inflammatory

parameters at baseline and 1 year We could not assess brain volume




analysis


















No 35 33 33 33 38 39

Mean age (SD) y 293 (73) 301 (97) 307 (80) 304 (82) 307 (75) 316 (82)

Females n () 24 (686) 26 (788) 21 (636) 24 (727) 28 (737) 32 (821)



Optic nerve 10 (286) 22 (667) 11 (333) 20 (606) 10 (263) 24 (615)

Brainstem 9 (257) 5 (152) 7 (212) 7 (212) 8 (211) 4 (103)

Spinal cord 11 (314) 4 (121) 10 (303) 4 (121) 14 (368) 3 (77)

Other 5 (143) 2 (61) 5 (152) 2 (61) 6 (158) 8 (205)




















Noa 39 39 39 38 38 40 38 33 30 21 21 23 22 21 18

rb 0595 0617 0538 0619 0649 0492 0456 20558 20345 0570 0609 0589 0167 20892 20842

p Value 00001 00001 00001 00001 00001 0001 0004 0001 0072 0007 0003 0003 0456 00001 00001





















Conversion to CDMS

Univariate analysis

DMTb 0701 1126 0615ndash2062


NfL-100c 00001 1009 1005ndash1014

OCBs 00001 6074 2580ndash14300




NfL-100 0040 1005 1000ndash1011

OCBs 0048 2597 1009ndash6683




Univariate analysis

DMT 0292 0736 0416ndash1302

NfL-100 00001 1009 1005ndash1013


OCBs 00001 8427 4189ndash16951




NfL-100 0155 1004 0999ndash1008

OCBs 0012 2669 1236ndash5762












































































































Basel Switzerland

































































576ndash578












S208ndashS219







Brain 20071302554ndash2565




201319157ndash164







2003611720ndash1725




2004631586ndash1590




13081ndash89



233183ndash198












































262113ndash120




























201016287ndash292



35223ndash31




201687126ndash129


























Errata





Reprints














1159ndash1163


















analysis


















No 35 33 33 33 38 39

Mean age (SD) y 293 (73) 301 (97) 307 (80) 304 (82) 307 (75) 316 (82)

Females n () 24 (686) 26 (788) 21 (636) 24 (727) 28 (737) 32 (821)



Optic nerve 10 (286) 22 (667) 11 (333) 20 (606) 10 (263) 24 (615)

Brainstem 9 (257) 5 (152) 7 (212) 7 (212) 8 (211) 4 (103)

Spinal cord 11 (314) 4 (121) 10 (303) 4 (121) 14 (368) 3 (77)

Other 5 (143) 2 (61) 5 (152) 2 (61) 6 (158) 8 (205)




















Noa 39 39 39 38 38 40 38 33 30 21 21 23 22 21 18

rb 0595 0617 0538 0619 0649 0492 0456 20558 20345 0570 0609 0589 0167 20892 20842

p Value 00001 00001 00001 00001 00001 0001 0004 0001 0072 0007 0003 0003 0456 00001 00001





















Conversion to CDMS

Univariate analysis

DMTb 0701 1126 0615ndash2062


NfL-100c 00001 1009 1005ndash1014

OCBs 00001 6074 2580ndash14300




NfL-100 0040 1005 1000ndash1011

OCBs 0048 2597 1009ndash6683




Univariate analysis

DMT 0292 0736 0416ndash1302

NfL-100 00001 1009 1005ndash1013


OCBs 00001 8427 4189ndash16951




NfL-100 0155 1004 0999ndash1008

OCBs 0012 2669 1236ndash5762












































































































Basel Switzerland

































































576ndash578












S208ndashS219







Brain 20071302554ndash2565




201319157ndash164







2003611720ndash1725




2004631586ndash1590




13081ndash89



233183ndash198












































262113ndash120




























201016287ndash292



35223ndash31




201687126ndash129


























Errata





Reprints














1159ndash1163






























Noa 39 39 39 38 38 40 38 33 30 21 21 23 22 21 18

rb 0595 0617 0538 0619 0649 0492 0456 20558 20345 0570 0609 0589 0167 20892 20842

p Value 00001 00001 00001 00001 00001 0001 0004 0001 0072 0007 0003 0003 0456 00001 00001





















Conversion to CDMS

Univariate analysis

DMTb 0701 1126 0615ndash2062


NfL-100c 00001 1009 1005ndash1014

OCBs 00001 6074 2580ndash14300




NfL-100 0040 1005 1000ndash1011

OCBs 0048 2597 1009ndash6683




Univariate analysis

DMT 0292 0736 0416ndash1302

NfL-100 00001 1009 1005ndash1013


OCBs 00001 8427 4189ndash16951




NfL-100 0155 1004 0999ndash1008

OCBs 0012 2669 1236ndash5762












































































































Basel Switzerland

































































576ndash578












S208ndashS219







Brain 20071302554ndash2565




201319157ndash164







2003611720ndash1725




2004631586ndash1590




13081ndash89



233183ndash198












































262113ndash120




























201016287ndash292



35223ndash31




201687126ndash129


























Errata





Reprints














1159ndash1163
































Conversion to CDMS

Univariate analysis

DMTb 0701 1126 0615ndash2062


NfL-100c 00001 1009 1005ndash1014

OCBs 00001 6074 2580ndash14300




NfL-100 0040 1005 1000ndash1011

OCBs 0048 2597 1009ndash6683




Univariate analysis

DMT 0292 0736 0416ndash1302

NfL-100 00001 1009 1005ndash1013


OCBs 00001 8427 4189ndash16951




NfL-100 0155 1004 0999ndash1008

OCBs 0012 2669 1236ndash5762












































































































Basel Switzerland

































































576ndash578












S208ndashS219







Brain 20071302554ndash2565




201319157ndash164







2003611720ndash1725




2004631586ndash1590




13081ndash89



233183ndash198












































262113ndash120




























201016287ndash292



35223ndash31




201687126ndash129


























Errata





Reprints














1159ndash1163

























Conversion to CDMS

Univariate analysis

DMTb 0701 1126 0615ndash2062


NfL-100c 00001 1009 1005ndash1014

OCBs 00001 6074 2580ndash14300




NfL-100 0040 1005 1000ndash1011

OCBs 0048 2597 1009ndash6683




Univariate analysis

DMT 0292 0736 0416ndash1302

NfL-100 00001 1009 1005ndash1013


OCBs 00001 8427 4189ndash16951




NfL-100 0155 1004 0999ndash1008

OCBs 0012 2669 1236ndash5762












































































































Basel Switzerland

































































576ndash578












S208ndashS219







Brain 20071302554ndash2565




201319157ndash164







2003611720ndash1725




2004631586ndash1590




13081ndash89



233183ndash198












































262113ndash120




























201016287ndash292



35223ndash31




201687126ndash129


























Errata





Reprints














1159ndash1163























































































































Basel Switzerland

































































576ndash578












S208ndashS219







Brain 20071302554ndash2565




201319157ndash164







2003611720ndash1725




2004631586ndash1590




13081ndash89



233183ndash198












































262113ndash120




























201016287ndash292



35223ndash31




201687126ndash129


























Errata





Reprints














1159ndash1163







































































576ndash578












S208ndashS219







Brain 20071302554ndash2565




201319157ndash164







2003611720ndash1725




2004631586ndash1590




13081ndash89



233183ndash198












































262113ndash120




























201016287ndash292



35223ndash31




201687126ndash129


























Errata





Reprints














1159ndash1163

























262113ndash120




























201016287ndash292



35223ndash31




201687126ndash129


























Errata





Reprints














1159ndash1163




































Errata





Reprints














1159ndash1163































Errata





Reprints














1159ndash1163



























1159ndash1163

















Neurofilament light chain level is a weak risk factor for ... · risk factor for the development of MS ABSTRACT Objective: To determine the prognostic value of selected biomarkers

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