Circulating miR-150 in CSF is a novel candidate biomarker for … · candidate biomarker for...

Petra Bergman PhDEliane PiketMohsen Khademi PhDTojo JamesLou Brundin MD PhDTomas Olsson MD PhDFredrik Piehl MD PhDMaja Jagodic PhD

Correspondence toDr Jagodicmajajagodickise

Supplemental dataat Neurologyorgnn

Circulating miR-150 in CSF is a novelcandidate biomarker for multiple sclerosis

ABSTRACT

Objective To explore circulating microRNAs (miRNAs) in cell-free CSF as novel biomarkers formultiple sclerosis (MS)

Methods Profiling of miRNAs in CSF of pooled patients with clinically isolated syndrome (CIS)patients with relapsing-remitting MS and inflammatory and noninflammatory neurologic diseasecontrols was performed using TaqMan miRNA arrays Two independent patient cohorts (n 5 142and n 5 430) were used for validation with real-time PCR

Results We reliably detected 88 CSF miRNAs in the exploratory cohort Subsequent validation in2 cohorts demonstrated significantly higher levels of miR-150 in patients with MS HighermiR-150 levels were also observed in patients with CIS who converted to MS compared to non-converters and in patients initiating natalizumab treatment Levels of miR-150 correlated withimmunologic parameters including CSF cell count immunoglobulin G index and presence ofoligoclonal bands and with candidate protein biomarkers C-X-C motif chemokine 13 matrix met-allopeptidase 9 and osteopontin Correlation with neurofilament light chain (NFL) was observedonly when NFL was adjusted for age using a method that requires further validation AdditionallymiR-150 discriminated MS from controls and CIS converters from nonconverters equally well asthe most informative protein biomarkers Following treatment with natalizumab but not fingoli-mod CSF levels of miR-150 decreased while plasma levels increased with natalizumab anddecreased with fingolimod suggesting immune cells as a source of miR-150

Conclusions Our findings demonstrate miR-150 as a putative novel biomarker of inflammatoryactive disease with the potential to be used for early diagnosis of MS

Classification of evidence This study provides Class II evidence that CSF miR-150 distinguishespatients with MS from patients with other neurologic conditions Neurol Neuroimmunol

Neuroinflamm 20163e219 doi 101212NXI0000000000000219

GLOSSARYAUC 5 area under the curve CIS 5 clinically isolated syndrome CXCL13 5 C-X-C motif chemokine 13 DMD 5 disease-modifying drug EDSS 5 Expanded Disability Status Scale IgG 5 immunoglobulin G INDC 5 inflammatory neurologicdisease controls miRNA 5 microRNA MMP-9 5 matrix metallopeptidase 9 MS 5 multiple sclerosis NFL 5 neurofilamentlight chain NINDC 5 noninflammatory neurologic disease controls OCB 5 oligoclonal band OPN 5 osteopontin PBMC 5peripheral blood mononuclear cells ROC5 receiver operating characteristic RRMS5 relapsing-remitting multiple sclerosisRT 5 reverse transcription TLDA 5 TaqMan low density arrays

Multiple sclerosis (MS) is an immune-mediated demyelinating disease of the CNS that has dur-ing the last decades shifted from being a disease with very limited treatments to being amongthe most dynamic fields in clinical neurology regarding disease-modifying drugs (DMDs)While these drugs present new opportunities for personalized treatments they also increasethe need for reliable biomarkers to provide accurate diagnosis and prognosis and to predictresponse to treatments1 A large number of molecules detectable in blood or CSF has beensuggested to reflect different disease processes however few have been replicated in large andcontrolled cohorts which is necessary for potential clinical applications2

From the Department of Clinical Neuroscience Center for Molecular Medicine Karolinska Institutet Stockholm Sweden

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 Karolinska Institutet

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

MicroRNAs (miRNAs) are small 22nucleotide noncoding RNAs which regulategene expression in a post-transcriptional man-ner34 Besides intracellular functions cell-freemiRNAs have been detected in various bio-fluids5 where they are packaged in vesicles (exo-somes andmicrovesicles)6 and thereby protectedfrom degradation The potential for using cir-culating miRNAs as biomarkers for diagnosticprognostic and predictive applications has beena hot topic of investigation in many differentdiseases including MS7ndash10 At present only onestudy comprehensively investigated miRNAs inCSF from patients with MS and reported differ-ences in the levels of 3 miRNAs between pa-tients with MS and controls10

In this study we profiled circulating miRNAsin cell-free CSF in a large cohort of patients withMS and controls identifying miR-150 as a puta-tive novel biomarker for MS

METHODS Classification of evidence We included pa-

tients with relapsing-remitting MS (RRMS) and patients with

clinically isolated syndrome (CIS) with a diagnosis according to

the 2005 revisions to the McDonald criteria11 and neurologic

disease controls who displayed no clinical or neuroradiologic

features of MS Furthermore noninflammatory neurologic disease

controls (NINDC) had no inflammatory lesions on MRI and no

signs of intrathecal inflammation as shown by the presence of any of

the following oligoclonal bands (OCBs) increased immunoglobulin

G (IgG) index or pleocytosis (higher than 23 upper normal limit

ie 10000 cellsmL) Inflammatory neurologic disease controls

(INDC) may or may not have inflammatory lesions on MRI

together with the presence of intrathecal inflammation as defined

above The inclusion of samples into 4 different diagnostic categories

(CIS RRMS NINDC and INDC) was based on obtaining

a comparable group size age female-to-male ratio and the period

of sampling among the 4 categories The miR-150 assays were

carried out on randomized samples in a blinded fashion and the

quantification analysis of miR-150 levels was performed by 2

people independently who were blind to the diagnostic status of

the samples

The objective of this study was to profile circulating miRNAs

in cell-free CSF in a large cohort of patients with MS and controls

to identify a novel biomarker for MS This study provides Class II

evidence

Patients During routine visits to the neurology clinic at Karo-

linska University Hospital patientsrsquo Expanded Disability Status

Scale (EDSS) score was determined by the treating neurologist

and CSF and blood samples were collected Patients were subdi-

vided into RRMS CIS INDC and NINDC MRI examinations

on 15T or 3T scanners were done according to clinical routine

Here we collected information on number of T2 and gadolinium-

enhancing lesions as judged from the original neuroradiologic

evaluation of scans performed within 66 months of sampling

For detailed patient demographics see table 1

Handling of samples The CSF samples were centrifuged

immediately after lumbar puncture at 440g for 10 minutes at

room temperature to separate cells and larger particles from the

CSF supernatant The blood samples were collected in EDTA

tubes and centrifuged at 1500g for 15 minutes Both the plasma

phase and the CSF supernatant were batched and stored at

280degC until use Methodologic details regarding measurements

of C-X-C motif chemokine 13 (CXCL13) matrix metallopepti-

dase 9 (MMP-9) osteopontin (OPN) and neurofilament light

chain (NFL) in CSF can be found in the original study12 Levels

of miRNA in CSF and plasma of patients with MS were deter-

mined at baseline and 12 months after open-label treatment with

natalizumab or fingolimod

Standard protocol approvals registrations and patientconsents CSF and blood samples were handled according to

consensus guidelines13 The study was approved by the regional

ethical committee (ethical permit 20092107-312) and written

informed consent was obtained from all patients

RNA isolation from cell-free CSF For miRNA TaqMan low

density arrays (TLDA) 4 CSF pools were created by combining

equal volumes of CSF from patients with CIS (n5 15) MS (n5

15) NINDC (n 5 13) and INDC (n 5 14) RNA was isolated

from 500 mL using the miRCURY RNA isolation kit for biofluids

(Exiqon Vedbaek Denmark) according to manufacturerrsquos proto-

col For normalization of sample-to-sample variation 2 fmol

synthetic Arabidopsis thaliana miRNA ath-miR159a 59-

UUUGGAUUGAAGGGAGCUCUA-39 (RNA oligonucleotide

Eurofins Genomics Ebersberg Germany) was spiked into each

CSF pool after addition of Lysis Solution BF

In addition to TLDA cards where CSF pools were used indi-

vidual CSF samples used in the profiling pools (n 5 57) and

validation cohort 1 (n 5 142) were subjected to total RNA iso-

lation using a standard TRIzol protocol where 700 mL of TRIzol

reagent (Invitrogen Life Technologies Carlsbad CA) was added

to 300 mL CSF sample For normalization of sample-to-sample

variation 2 fmol synthetic Arabidopsis thaliana miRNA ath-miR159a was spiked into each CSF sample after the addition of

TRIzol

RNA isolation for validation cohort 2 (n5 450) and natalizu-

mab- (n 5 20) and fingolimod-treated (n 5 17) patients was

performed on 300 mL CSF using the miRCURY RNA isolation

kit for biofluids For normalization of sample-to-sample variation

synthetic Caenorhabditis elegans miRNAs cel-miR-39 59-UCA

CCG GGU GUA AAU CAG CUU G-39 cel-miR-54 59-UACCCG UAA UCU UCA UAA UCC GAG-39 cel-miR-238 59-UUU GUA CUC CGA UGC CAU UCA GA-39 (RNA oligonu-

cleotides Integrated DNA Technologies Coralville IA) were

added as a mixture of 3 fmol per oligonucleotide to each denatured

sample All eluted RNA was immediately stored at 280degC

RNA isolation from cell-free plasma RNA isolation from

natalizumab- (n 5 17) and fingolimod-treated (n 5 17)

patients as well as a plasma cohort (n 5 156) was performed

from 100 mL plasma using the miRCURY RNA isolation

kit for biofluids according to manufacturerrsquos protocol For

normalization of sample-to-sample variation synthetic

Caenorhabditis elegans miRNAs cel-miR-39 cel-miR-54 and cel-miR-238 were added as a mixture of 15 fmol per oligonucleotide

to each denatured sample Eluted RNA was immediately stored

at 280degC

MiRNA profiling with TLDA MiRNA was reverse tran-

scribed using Megaplex RT Primers Human Pool Set v30

and TaqMan MicroRNA Reverse Transcription Kit (Applied Bi-

osystems Life Technologies) according to manufacturerrsquos instruc-

tions The reverse transcription (RT) products were preamplified

2 Neurology Neuroimmunology amp Neuroinflammation


using Megaplex PreAmp Primers Human Pool Set v30 and

TaqMan PreAmp Master Mix Kit The preamplified (PreAmp)

products were loaded onto TLDA cards (TaqMan Array Human

MicroRNA A1B Cards Set v30) and run on the ABI 7900HT

real-time PCR system Raw data were analyzed using the

ExpressionSuite Software (Life Technologies) To ensure good

quality detection and to avoid false-positives a stringent cutoff

for detection was set where at least 2 samples should have Ct

32 AmpScore 11 and minimum 2 samples with adequate

Cq Confidence (AmpScore and Cq Confidence were provided

by ExpressionSuite software) Cutoff thresholds were set in

consultation with technical experts at Applied Biosystems Raw

Ct values were normalized to the spike-in control using the

following equation normalized sample Ct 5 raw sample Ct 2

(spike-in Ct value for sample 2 average of all spike Ct values) A

and B cards were normalized separately

Quantitative real-time PCR Multiplexed RT and preamplifi-

cation products were created using the Protocol for Creating Cus-

tom RT and Preamplification Pools using TaqMan MicroRNA

Assays (publication 4465407 Applied Biosystems) Preamplified

products were diluted 83 in 013TE prior to real-time PCR

using individual miRNA assays on the CFX384 real-time PCR

detection system (Bio-Rad Hercules CA) Individuals with

undetectable miRNA levels were excluded from analysis Raw

data were analyzed and Ct values extracted using CFX Manager

software For validation cohort 1 miRNA levels were calculated

using the following equation DCt 5 Ct miRNA 2 Ct ath-

miR159a DDCt 5 2^ 2(DCt 2 Avg DCt) All DDCt values

were normalized to the lowest DDCt For validation cohort 2

treatment and plasma cohorts 3 interplate controls were run for

each miRNA assay on each plate to adjust for plate-to-plate

variations MiRNA levels were calculated using the following

equation DCt 5 Ct miRNA 2 Ct Avg spike-in DDCt 5 2^

2(DCt 2 Avg DCt) All DDCt values were normalized to the

lowest DDCt

Statistical analysis Qualitative data were analyzed using

Kruskal-Wallis one-way analysis of variance combined with the

Dunn test of multiple comparisons For 2-group comparisons

Mann-Whitney U test was used Wilcoxon signed rank test for

matched pairs was used to analyze the treatment cohort All

correlations were performed on ln-transformed values (ln[x 1 1]

transformation was applied for all parameters apart from NFL

adjusted for age-related changes where ln[x 1 281] was used)

and analyzed using Spearman rank test All statistical analyses

were performed using GraphPad Prism 5 (San Diego CA) NFL

adjustment for age-related changes was performed by subtracting

the expected level for the given age calculated following linear

relationship reported in healthy individuals (ie 118 ngL 3 age

2 95 ngL23) from the measured NFL level

Receiver operating characteristic (ROC) curve analyses

between MS and NINDC as well as CIS and CIS-MS were per-

formed using pROC and Epi packages in R Independent contri-

bution of multiple variables was tested using generalized linear

model in Rcmdr package in R

RESULTS Detection of miRNAs in cell-free CSF Pro-filing of miRNAs using TLDA cards enables quanti-fication of the 754 most common human miRNAsWe profiled miRNAs in pooled samples from CIS(n 5 15) MS (n 5 15) and controls (NINDCn 5 13 and INDC n 5 14) and we identified 88miRNAs in cell-free CSF (63 miRNAs passed the

Tab

le1

Pat

ient

dem

ogra

phics

Poo

lValidat

ionco

hort

1Validat

ionco

hort

2Tre

atmen

tco

hort

Nat

alizum

ab

Tre

atmen

tco

hort

Fingolim

od

CIS

MS

NIN

DC

INDC

CIS

MS

NIN

DC

INDC

CIS

MS

NIN

DC

INDC

CSF

Plasm

aCSF

Plasm

a

Tot

alno

ofpat

ient

s15

15

13

14

34

43

34

31

96

120

119

95

20

17

17

Fem

alemale

132

123

94

113

241

0261

7241

0211

0712

5823

8823

7653

0127

125

125

Age

ymed

ian(ran

ge)

31

(20ndash61)

30

(22ndash56)

36

(36ndash55)

34

(21ndash58)

36

(21ndash52)

37

(18ndash61)

35

(21ndash63)

45

(13ndash64)

32

(16ndash60)

37

(18ndash73)

38

(21ndash72)

40

(21ndash71)

37

(23ndash53)

37

(23ndash53)

37(27ndash59)

EDSSm

edian(ran

ge)

1(0ndash3)

35

(15ndash6)

NA

NA

2(0ndash65)

25

(1ndash75)

NA

NA

1(0ndash6)

2(0ndash75)

1(0ndash6)

1(0ndash3)

38

(1ndash75)

45

(2ndash75)

2(1ndash65)

Disea

sedur

ations

(ons

et-to-sa

mplin

g)y

med

ian(ran

ge)

0(0ndash14)

4(0ndash9)

NA

NA

1(0ndash18)

7(0ndash40)

NA

NA

0(0ndash11)

6(0ndash46)

2(0ndash44)

2(0ndash56)

95

(1ndash26)

9(1ndash17)

13

(2ndash23)

Per

cent

sampleddur

ing

relapse

(n)

20

(15)

100

(15)

NA

NA

20

(34)

26

(43)

NA

NA

26

(96)

31

(120)

NA

NA

15

(20)

12

(17)

6(17)

OCB-pos

itive(n)

86

(14)

93

(14)

0(12)

0(6)

45

(31)

88

(43)

0(31)

9(22)

71

(49)

82

(105)

0(64)

13

(31)

85

(20)

88

(17)

88

(17)

CSFmon

onuc

lear

cells

med

ian(ran

ge)

8(3ndash36)

7(1ndash90)

2(0ndash5)

1(0ndash17)

25

(0ndash92)

6(0ndash40)

2(0ndash7)

2(0ndash15)

4(0ndash36)

4(0ndash40)

1(0ndash11)

2(0ndash433)

6(1ndash34)

55

(1ndash34)

2(0ndash14)

Per

cent

conv

erte

dCIS

60

NA

NA

NA

NA

NA

NA

NA

63

NA

NA

NA

NA

NA

NA

Abb

reviations

CIS

5clinically

isolated

synd

rome

EDSS

5Exp

ande

dDisab

ility

StatusSca

leIN

DC

5inflam

matoryne

urolog

icdise

aseco

ntrolsMS

5multiplesc

lerosis

NA

5no

tap

plicab

leNIN

DC

5no

n-inflam

matoryne

urolog

icdise

aseco

ntrolsO

CB

5oligoc

lona

lban

ds

The(n)ind

icates

numbe

rof

samples

forwhich

theinform

ationwas

available

Neurology Neuroimmunology amp Neuroinflammation 3


most stringent detection cutoff and an additional 25miRNAs were detected when allowing for reducedamplification quality in maximum 2 samples) (tablee-1 at Neurologyorgnn) Subsequently 15 miRNAswere selected based on quantifiable levels (detectionin at least 75 of the individual samples of theprofiling pools) and an indication of a largerdifference between MS and NINDC (table e-1) forexamination in an independent sample cohort(validation cohort 1 n 5 142) Out of the testedmiRNAs only miR-145 and miR-150 displayedsignificant differences between MS and NINDC(p 5 00038 and p 5 00027 respectively) (figuree-1) Together these results demonstrate detectabilityof circulating miRNAs in cell-free CSF anddifferential presence of miR-145 and miR-150

Levels of miR-150 are elevated in patients with MS and

associate with markers of inflammationWe next soughtto determine whether the observed differences couldbe confirmed in a larger cohort validation cohort 2(n 5 430) MiR-145 was particularly interesting asit had been reported as a biomarker of MS in plasmaand serum714 as well as in peripheral bloodmononuclear cells (PBMC)715 MiR-150 has not beenreported in MS biofluids but is differentially regulatedalbeit in small cohorts in PBMC and T cells1617 In thislarge cohort we could replicate significantly higherlevels of miR-150 in MS compared to both controlgroups as well as between CIS and NINDC (p

00001) (figure 1A) Notably however we were notable to reproduce the differences observed for miR-145 (p 5 073) (figure 1B) We also observed highermiR-150 levels in CSF from patients with CIS whosubsequently converted to MS (CIS-MS) compared tothose who did not convert during follow-up (medianperiod of 52 months) (p 00001) (figure 1C) Toevaluate the diagnostic value of miR-150 indifferentiating patients with MS and controls weconstructed a ROC curve (figure 1D) Area under thecurve (AUC) for miR-150 was 0744 (50 specificityand 89 sensitivity)

To explore the relation of miR-150 to MS diseaseprocesses we correlated miR-150 with established labora-tory markers of disease We observed significantly higherlevels of miR-150 in patients with OCBs compared toOCB-negative patients (p 5 00003) (figure 1E) Highlevels of miR-150 correlated with higher CSF cell num-bers (p 00001 r5 033) and higher IgG index (p00001 r 5 033) (table 2) indicating that miR-150associates with active inflammation In contrast miR-150 levels did not correlate with the number of MRIT2 lesions and EDSS score (figure 1F table 2) and therewas only a tendency for higher miR-150 levels in relapse(p 5 01) (figure 1G) However patients with RRMSwho subsequently initiated treatment with natalizumab

displayed higher levels compared to all other patients withRRMS (p 5 0022) (figure 1H) and this effect wasindependent from the number of MRI T2 lesions(p5 0038) Finally we also investigated the relationshipbetween miR-150 levels and candidate CSF biomarkersfor MS CXCL13 MMP-9 OPN and NFL Weobserved that higher levels of miR-150 correlate withhigher levels of CXCL13 (p 00001 r 5 044)MMP-9 (p 00001 r 5 031) and OPN (p 5

0008 r5 026) (table 2) Together these results indicatethat miR-150 is a marker of CNS inflammation

Effect of DMDs on miR-150 levels in CSF and plasma

Well-established DMDs with known actions includenatalizumab and fingolimod Patients treated withnatalizumab displayed a significant reduction ofCSF miR-150 levels after 12 months of treatment(figure 2A) Concomitantly an increase in plasmalevels of miR-150 was found in these patients(figure 2B) A divergent pattern was observed inpatients initiating fingolimod where plasma miR-150 levels decreased following treatment while CSFlevels remained unchanged (figure 2CD) Thefindings of regulated miR-150 levels in plasmafollowing treatment raised the question of whethermiR-150 could act as a biomarker for MS also inplasma To investigate this we analyzed 156patients and controls from validation cohort 2 fromwhom plasma samples were available However wecould not observe differences in miR-150 levelsbetween any of the disease groups (data not shown)This suggests that the treatments affect levels of miR-150 but that plasma levels of miR-150 are unlikely toserve as a marker of MS

Ratio of miR-150 and miR-204 as a biomarker in CSF

The rationale for spiking CSF samples with syntheticmiRNAs is the absence of circulating endogenousmiRNA for normalization1819 An alternative is to usemiRNA pairs20 where the ratio (DCt) of all miRNAsare calculated and the pair that provides the highestaccuracy in differentiating patients and controls isselected We performed this comparison for themiRNAs in validation cohort 1 and established thatthe pair of miR-150 and miR-204 provides thelargest difference between MS and NINDC (tablee-2) Levels of miR-150 normalized with miR-204were significantly higher in MS compared to NINDCand INDC in validation cohort 2 (figure 3A) as well asin patients with CIS who subsequently converted toMS compared to those who did not convert (p

00001) (figure 3B) The miR-150miR-204 ratioalso displayed a stronger correlation compared to miR-150 alone with candidate CSF biomarkers (especiallyCSF cells CXCL13 and MMP-9) including significantcorrelation with age-adjusted NFL levels (p 0007r 5 021) (table 2) Additionally AUC identifies



Figure 1 Levels of miR-150 are elevated in patients with multiple sclerosis (MS) and patients with clinicallyisolated syndrome (CIS) who convert to MS

Relative levels of mature microRNAs (miRNAs) were measured using multiplexed specific TaqMan miRNA assays and nor-malized to an average of 3 spike-ins (cel-miR-39 cel-miR-54 and cel-miR-238) Levels of (A) miR-150 are significantly dif-ferent between disease groups while (B) there was no difference between levels of miR-145 Levels of miR-150 are also (C)higher in patients with CIS who converted to MS (CIS-MS) compared to those who never converted and (D) can discriminateMS from noninflammatory neurologic disease controls (NINDCs) based on receiver operating characteristic (ROC) curveanalysis Graph intersection indicates the cutoff value for miR-150 that proved the best specificity and sensitivity Levelsof miR-150 in relation to descriptive disease parameters (E) oligoclonal bands (OCB) (F) relapse and remission (G) number ofMRI lesions and (H) subsequent treatment with natalizumab Lines in dot plots represent median and interquartile rangep 005 p 001 p 0001 INDC 5 inflammatory neurologic disease controls



miR-150miR-204 ratio as a better marker indifferentiating MS and NINDC (AUC 0811 79specificity and 71 sensitivity) (figure 3C) comparedto miR-150 normalized to spike-ins In this respectmiR150miR-204 ratio performed as well as thecurrent best protein biomarker CXCL13 (figure e-2A)Finally miR-150miR-204 ratio could differentiatepatients with CIS who converted to MS compared tothose who did not convert (AUC5 0775) and had anindependent effect (p5 0017) from the factors knownto affect conversion namely age OCB status and MRI

lesions (figure 3D) Even in this respect the miR-150miR-204 ratio performed similarly to informativeprotein biomarkers CXCL13 and MMP-9 while NFLhad no predictive power (figure e-2B) Together thisdemonstrates the potential for using the miR-150miR-204 ratio as a biomarker for discriminatingpatients with MS from controls and patients with CISthat will convert to MS

DISCUSSION In the last few years circulatingmiRNAs have become a new class of biomarkers for

Table 2 Correlations with clinical and paraclinical parameters and candidate biomarkers

Age IgG index CSF cellsGd1lesions

MRIlesions EDSS

EDSSlatest CXCL13 MMP-9 OPN NFL NFLadj

miR-150 vs cel

No 181 170 180 142 180 179 164 125 162 104 162 162

R 2018 033a 033a 005 2002 2003 2001 044a 031a 026ab 007 014

p Value 002 00001a 00001a 053 080 064 092 00001a 00001a 0008a 040 008

miR-150 vs 204

No 181 170 180 142 180 179 164 125 162 104 162 162

R 2022a 032a 046a 002 2007 2012 2007 060a 054a 020 015 021a

p Value 0002a 00001a 00001a 078 034 012 037 00001a 00001a 004 006 0007a

CXCL13

No 129 120 128 106 128 127 114 129 124 91 124 124

R 2037a 057a 064a 023 001 2004 004 1 069a 025 033a 043a

p Value 00001a 00001a 00001a 002 092 066 070 00001a 002 00002a 00001a

MMP-9

No 168 157 167 135 168 166 151 168 110 168 168

R 2031a 050a 049a 012 2020a 2021ab 2016 1 007 2001 007

p Value 00001a 00001a 00001a 018 0009a 0006a 006 049 093 040

OPN

No 110 102 110 82 110 109 104 110 110 110

R 019 019 022 032ac 021 020 026a 1 025ac 022

p Value 005 005 002 0004a 003 004 0007a 0009a 002

NFL

No 168 157 167 135 168 166 151 168 168

R 000 2000 013 028a 027a 023a 023a 1 097a

p Value 098 098 009 0001a 00005a 0003a 0005a 00001a

NFLadj

No 168 157 167 135 168 166 151 168

R 2018 006 024a 029a 024a 017 016 1

p Value 002 043 0002a 00007a 0002a 003 005

Abbreviations CXCL13 5 C-X-C motif chemokine 13 EDSS 5 Expanded Disability Status Scale Gd1 5 gadolinium-enhancing IgG 5 immunoglobulin GMMP-9 5 matrix metallopeptidase 9 NFL 5 neurofilament light chain OPN 5 osteopontinCorrelations were performed on ln-transformed values (ln[x 1 1] was used for all parameters apart from NFLadj where ln[x 1 281] was applied) andanalyzed using Spearman rank test NFLadj 5 NFL (measured) 2 118 3 age 2 95 (based on the linear relationship between NFL levels and age)23 Gd1lesions were evaluated in the period of 6 months from the time of samplinga Strong correlationsbStronger correlation in remission (data not shown)c Stronger correlation in relapse (data not shown)



various diseases including CNS disorders In thisstudy using an unbiased exploratory approach withsubsequent validation in 2 large cohorts we identifiedCSF levels of circulating miR-150 as a promisingcandidate biomarker for MS

We identified higher levels of circulating miR-150in CSF of patients with MS compared to both inflam-matory and noninflammatory controls in 2 cohortsjointly comprising nearly 600 individuals The levelsof miR-150 correlated with established immunologicparameters ie CSF cell numbers IgG index pres-ence of OCB as well as the candidate immune-associated biomarkers CXCL13 MMP-9 and OPNThe strongest correlation was observed with CXCL13and MMP-9 suggesting that miR-150 reflects similarqualities of the immune responses We also observedcorrelation with NFL which is released during ongo-ing axonal injury eg upon inflammatory attack21

and is a marker of disease activity in MS22 but onlyafter adjusting levels of NFL for age-related changes23

However correlation with NFL should be taken withcaution considering the novelty of our approach to age-adjust NFL levels which requires further validationTogether these results indicate that miR-150 isa marker of CNS inflammation in the context of

MS Additionally miR-150 was higher in patients withCIS who converted to MS compared to those who didnot convert during follow-up indicating a potential tofacilitate earlier diagnosis The observation that miR-150 is not immediately affected by disease dynamicsie relapse vs remission suggests that it may serve asa more stable prognostic marker than for instanceCXCL13 and NFL which are both upregulated dur-ing relapses (p5 001 and 002 respectively) Accord-ingly we detected higher levels of miR-150 in patientswho were subsequently treated with natalizumab sug-gesting that higher miR-150 levels associate with moreinflammatory active disease

Previously 63 miRNAs were reported to be differ-entially expressed between MS lesions and healthywhite matter24 Nearly 40 of these miRNAs werealso detected in our study indicating that circulatingmiRNAs in the CSF may mirror events in the targettissue Surprisingly we could not detect any of the 3miRNAs (miR-181c miR-633 and miR-922)10 pre-viously reported to be differentially regulated in CSFof patients with MS This lack of overlap between thestudies probably reflects differences in separation ofcells from the cell-free CSF fraction Several recentstudies report miR-150 among the more abundant

Figure 2 Levels of miR-150 are altered in CSF and plasma following treatment with disease-modifying drugs

Relative levels of mature miR-150 were measured in CSF and in plasma from patients with multiple sclerosis treated with(AB) natalizumab and (CD) fingolimod at baseline and at 12 months Quantification was performed using multiplexed spe-cific TaqMan microRNA assays and normalized to an average of 3 spike-ins (cel-miR-39 cel-miR-54 and cel-miR-238)p 005 p 001 p 0001



miRNAs in cell-free CSF using different methods25ndash28

corroborating our method of measuring circulatingmiRNAs in cell-free CSF which is handled accordingto consensus guidelines13

Although it is challenging to establish the sourceof circulating miRNAs our data suggest that immunecells release miR-150 Thus natalizumab reduced

miR-150 levels in the CSF with a concurrent increaseof miR-150 levels in plasma which parallels drug-induced changes in immune cell numbers in the 2compartments29 Along this line we also observedreduced levels of miR-150 in plasma in patients onfingolimod treatment reflecting sequestration ofimmune cells within secondary lymphoid organs30

Figure 3 MicroRNA (miRNA) pairs can be used to normalize miRNA levels

The ratio of miR-150 and miR-204 calculated and normalized using the DDCT method (see Methods) is significantlydifferent (A) between disease groups and (B) between patients with clinically isolated syndrome (CIS) who have convertedor not converted to multiple sclerosis (MS) The miR-150miR-204 ratio improves (C) the area under receiver operatingcharacteristic (ROC) (AUC) curve indicating improved specificity and sensitivity to discriminate MS from noninflammatoryneurologic disease controls (NINDC) compared tomiR-150 normalized to spike-ins The miR-150204 ratio can furthermore(D) predict conversion from CIS to MS as indicated by the ROC curve generated to compare converters and nonconvertersThe miR-150miR-204 ratio is an independent significant (p5 0017) predictor of conversion when known risk factors suchas age oligoclonal bands (OCB) and MRI lesions are taken into account and it can improve their combined predictive valueLines represent (A B) median and interquartile range p 001 p 0001 INDC 5 inflammatory neurologic diseasecontrols



It has been shown that activated monocytes and Tand B cells selectively package and secrete miR-150 inmicrovesicles3132 All these cell types are found inCSF and CNS of patients with MS33 and could thuscontribute to miR-150 release although the exactsource remains to be defined

Functional studies of intracellular miR-150 suggesta role in regulating T- and B-cell development34ndash37however the functionality of circulating miRNAs isfar from clarified They might mediate cell-to-cell com-munication3839 eg lymphocyte-derived exosomes areknown to transfer miRNAs to CD81 T cells andantigen-presenting cells38 Our observation of higherlevels of extracellular miR-150 compared to previousreports of reduced levels of miR-150 in PBMCs16 andT cells17 in patients with MS suggests that packaging ofmiR-150 is likely an active process and that exportedmiR-150 may have functional roles It has been shownthat infiltrating monocytes actively secrete miR-150thereby affecting endothelial cells3239 However anyfunctional implications of circulating miR-150 inMS remain to be investigated

Given the heterogeneity and complexity of MS it isunlikely that a single biomarker will be able to satisfyall needs for disease monitoring Our data indicate thatcandidate biomarkers while largely overlapping alsoreflect slightly different qualities of inflammatory re-sponses (table 2) and while some can discriminateMS from controls (CXCL13 MMP-9 and NFL)others cannot (OPN) (figure e-2A) Similarly whileCXCL13 andMMP-9 can discriminate CIS convertersfrom nonconverters NFL has very little predictivevalue (figure e-2B) A panel of markers is more likelyto achieve sufficient sensitivity and specificity Indeedwe here show that the difference between miR-150and miR-204 has improved biomarker characteristicscompared to miR-150 alone which may reflect theregulation of both miRNAs or more accurate normal-ization compared to spike-ins Indeed the miR-150miR-204 ratio had very similar predictive capacity todiscriminate MS from controls compared to the cur-rent best protein biomarker that we tested CXCL13It also performed similarly to CXCL13 andMMP-9 indiscriminating CIS converters from nonconverters andit has an additive independent effect even compared toknown risk factors such as OCB and MRI lesions Atpresent most candidate biomarkers in MS both inserum and CSF are proteins2 Compared to proteinsassays to study miRNAs are easily multiplexed pro-viding a possibility to detect a broad spectrum of bio-markers from a single isolation procedure Thistogether with the extraordinary stability of circulatingmiRNAs even during unfavorable conditions40 makesmiRNAs attractive candidates for biomarker selection

Using large cohorts and an unbiased detectionstrategy we demonstrate the potential of miR-150

as an early marker of inflammatory active disease thatwarrants further investigation Future studies employ-ing broad screening methods in large cohorts hold thepotential to define novel sensitive and specific bio-markers based on panels of miRNAs

AUTHOR CONTRIBUTIONSDr Bergman designed the study performed experimental work contrib-

uted to statistical analyses interpreted data and wrote and edited the

manuscript E Piket contributed to experimental work and writing

and submission of the manuscript Dr Khademi managed samples

T James contributed to statistical analyses Prof Brundin contributed

to sample collection and data interpretation Prof Olsson contributed

to sample collection and data interpretation Prof Piehl contributed to

sample collection and data interpretation and critically revised the

manuscript Dr Jagodic designed the study supervised the study per-

formed statistical analysis interpreted data and wrote and edited the

manuscript

STUDY FUNDINGThis work was supported by grants from the Swedish Research Council

the Swedish Association for Persons with Neurological Disabilities the

Swedish Brain Foundation the Swedish Medical Society Petrus and

Augusta Hedlunds Foundation the regional agreement on medical train-

ing and clinical research (ALF) between Stockholm County Council and

Karolinska Institutet and AstraZeneca (AstraZeneca-Science for Life Lab-

oratory collaboration)

DISCLOSUREP Bergman reports no disclosures E Piket received research support

from Neuro Sweden M Khademi and T James report no disclosures

L Brundin is on the scientific advisory board for Genzyme and Biogen

received speaker honoraria from Biogen and Genzyme provided written

information for the Swedish MPA on MS treatment receives royalties

from the Swedish Brain Fund participated in an airline commercial

and received research support from Swedish MRC Karolinska Institutet

Stockholm County and Soderberg Foundation T Olsson served on the

scientific advisory boards for Merck-Serono Biogen Idec GenzymeSa-

nofi Aventis and Novartis received travel funding andor speaker hono-

raria from Novartis Biogen Idec Sanofi Aventis Merck Genzyme and

Medimmune was co-editor for Current Opinion in Immunology and

received research support from Merck Biogen Idec Sanofi Aventis

Bayer Novartis Astra Zeneca The Swedish Research Council EU

fp7 Euratrans Neuroinox combiMS Swedish Brain Foundation AFA

Foundation Knut and Alice Wallenberg Foundation Bayer Schering

GenzymeSanofi-Aventis Biogen Idec and Astra Zeneca F Piehl served

on the data safety monitoring committee for ParexelChugai and

received research support from Biogen Novartis Genzyme and Swedish

Medical Research Council M Jagodic is on the editorial board for

Physiological Genomics and received research support from Astra Zeneca

The Swedish Research Council ALF The Swedish Association for Per-

sons with Neurological Disabilities The Swedish Medical Society and

Petrus and Augusta Hedlunds Foundation Go to Neurologyorgnn for

full disclosure forms

Received October 2 2015 Accepted in final form February 1 2016

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rosis challenges and opportunities J Intern Med 2014

275364ndash381

2 Comabella M Montalban X Body fluid biomarkers in

multiple sclerosis Lancet Neurol 201413113ndash126

3 Bartel DP MicroRNAs genomics biogenesis mecha-

nism and function Cell 2004116281ndash297

4 Engels BM Hutvagner G Principles and effects of

microRNA-mediated post-transcriptional gene regulation

Oncogene 2006256163ndash6169



5 Weber JA Baxter DH Zhang S et al The microRNA

spectrum in 12 body fluids Clin Chem 2010561733ndash1741

6 Valadi H Ekstrom K Bossios A Sjostrand M Lee JJ

Lotvall JO Exosome-mediated transfer of mRNAs and

microRNAs is a novel mechanism of genetic exchange

between cells Nat Cell Biol 20079654ndash659

7 Gandhi R Healy B Gholipour T et al Circulating micro-

RNAs as biomarkers for disease staging in multiple sclero-

sis Ann Neurol 201373729ndash740

8 Fenoglio C Ridolfi E Cantoni C et al Decreased circu-

lating miRNA levels in patients with primary progressive

multiple sclerosis Mult Scler 2013191938ndash1942

9 Siegel SR Mackenzie J Chaplin G Jablonski NG

Griffiths L Circulating microRNAs involved in multiple

sclerosis Mol Biol Rep 2012396219ndash6225

10 Haghikia A Haghikia A Hellwig K et al Regulated mi-

croRNAs in the CSF of patients with multiple sclerosis

a case-control study Neurology 2012792166ndash2170

11 Polman CH Reingold SC Edan G et al Diagnostic

criteria for multiple sclerosis 2005 revisions to the

ldquoMcDonald Criteriardquo Ann Neurol 200558840ndash846

12 Khademi M Dring AM Gilthorpe JD et al Intense

inflammation and nerve damage in early multiple sclerosis

subsides at older age a reflection by cerebrospinal fluid

biomarkers PLoS One 20138e63172

13 Teunissen CE Petzold A Bennett JL et al A consensus

protocol for the standardization of cerebrospinal fluid col-

lection and biobanking Neurology 2009731914ndash1922

14 Sondergaard HB Hesse D Krakauer M Sorensen PS

Sellebjerg F Differential microRNA expression in blood

in multiple sclerosis Mult Scler 2013191849ndash1857

15 Keller A Leidinger P Lange J et al Multiple sclerosis

microRNA expression profiles accurately differentiate pa-

tients with relapsing-remitting disease from healthy con-

trols PLoS One 20094e7440

16 Martinelli-Boneschi F Fenoglio C Brambilla P et al Mi-

croRNA and mRNA expression profile screening in multiple

sclerosis patients to unravel novel pathogenic steps and iden-

tify potential biomarkers Neurosci Lett 20125084ndash8

17 Jernas M Malmestrom C Axelsson M et al MicroRNA

regulate immune pathways in T-cells in multiple sclerosis

(MS) BMC Immunol 20131432

18 Roberts TC Coenen-Stass AM Wood MJ Assessment of

RT-qPCR normalization strategies for accurate quantifica-

tion of extracellular microRNAs in murine serum PLoS

One 20149e89237

19 Kroh EM Parkin RK Mitchell PS Tewari M Analysis of

circulating microRNA biomarkers in plasma and serum

using quantitative reverse transcription-PCR (qRT-PCR)

Methods 201050298ndash301

20 Boeri M Verri C Conte D et al MicroRNA signatures in

tissues and plasma predict development and prognosis of

computed tomography detected lung cancer Proc Natl

Acad Sci USA 20111083713ndash3718

21 Povlishock JT Pathobiology of traumatically induced axo-

nal injury in animals and man Ann Emerg Med 199322

980ndash986

22 Lycke JN Karlsson JE Andersen O Rosengren LE Neu-

rofilament protein in cerebrospinal fluid a potential

marker of activity in multiple sclerosis J Neurol Neuro-

surg Psychiatry 199864402ndash404

23 Varinggberg M Norgren N Dring A et al Levels and age

dependency of neurofilament light and glial fibrillary

acidic protein in healthy individuals and their relation to

the brain parenchymal fraction PLoS One 201510

e0135886

24 Junker A Krumbholz M Eisele S et al MicroRNA pro-

filing of multiple sclerosis lesions identifies modulators of

the regulatory protein CD47 Brain 20091323342ndash3352

25 Bjersing JL Lundborg C Bokarewa MI Mannerkorpi K

Profile of cerebrospinal microRNAs in fibromyalgia PLoS

One 20138e78762

26 Holm A Bang-Berthelsen CH Knudsen S et al MiRNA

profiles in cerebrospinal fluid from patients with central

hypersomnias J Neurol Sci 2014347199ndash204

27 Denk J Boelmans K Siegismund C Lassner D Arlt S

Jahn H MicroRNA profiling of CSF reveals potential

biomarkers to detect Alzheimerrsquos disease PLoS One

201510e0126423

28 Burgos KL Javaherian A Bomprezzi R et al Identifica-

tion of extracellular miRNA in human cerebrospinal fluid

by next-generation sequencing RNA 201319712ndash722

29 Stuve O Marra CM Jerome KR et al Immune surveil-

lance in multiple sclerosis patients treated with natalizu-

mab Ann Neurol 200659743ndash747

30 Chun J Hartung HP Mechanism of action of oral fingo-

limod (FTY720) in multiple sclerosis Clin Neuropharma-

col 20103391ndash101

31 de Candia P Torri A Gorletta T et al Intracellular modu-

lation extracellular disposal and serum increase of MiR-150

mark lymphocyte activation PLoS One 20138e75348

32 Li J Zhang Y Liu Y et al Microvesicle-mediated transfer of

microRNA-150 from monocytes to endothelial cells pro-

motes angiogenesis J Biol Chem 201328823586ndash23596

33 Stangel M Fredrikson S Meinl E Petzold A Stuve O

Tumani H The utility of cerebrospinal fluid analysis in

patients with multiple sclerosis Nat Rev Neurol 20139

267ndash276

34 Xiao C Calado DP Galler G et al MiR-150 controls B

cell differentiation by targeting the transcription factor c-

Myb Cell 2007131146ndash159

35 Zhou B Wang S Mayr C Bartel DP Lodish HF miR-

150 a microRNA expressed in mature B and T cells

blocks early B cell development when expressed prema-

turely Proc Natl Acad Sci USA 20071047080ndash7085

36 Ghisi M Corradin A Basso K et al Modulation of

microRNA expression in human T-cell development

targeting of NOTCH3 by miR-150 Blood 2011117

7053ndash7062

37 Trifari S Pipkin ME Bandukwala HS et al MicroRNA-

directed program of cytotoxic CD81 T-cell differentia-

tion Proc Natl Acad Sci USA 201311018608ndash18613

38 Mittelbrunn M Gutierrez-Vazquez C Villarroya-Beltri C

et al Unidirectional transfer of microRNA-loaded exo-

somes from T cells to antigen-presenting cells Nat Com-

mun 20112282

39 Zhang Y Liu D Chen X et al Secreted monocytic miR-

150 enhances targeted endothelial cell migration Mol Cell

201039133ndash144

40 Chen X Ba Y Ma L et al Characterization of micro-

RNAs in serum a novel class of biomarkers for diagnosis

of cancer and other diseases Cell Res 200818997ndash1006



DOI 101212NXI000000000000021920163 Neurol Neuroimmunol Neuroinflamm

Petra Bergman Eliane Piket Mohsen Khademi et al Circulating miR-150 in CSF is a novel candidate biomarker for multiple sclerosis

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

MicroRNAs (miRNAs) are small 22nucleotide noncoding RNAs which regulategene expression in a post-transcriptional man-ner34 Besides intracellular functions cell-freemiRNAs have been detected in various bio-fluids5 where they are packaged in vesicles (exo-somes andmicrovesicles)6 and thereby protectedfrom degradation The potential for using cir-culating miRNAs as biomarkers for diagnosticprognostic and predictive applications has beena hot topic of investigation in many differentdiseases including MS7ndash10 At present only onestudy comprehensively investigated miRNAs inCSF from patients with MS and reported differ-ences in the levels of 3 miRNAs between pa-tients with MS and controls10

In this study we profiled circulating miRNAsin cell-free CSF in a large cohort of patients withMS and controls identifying miR-150 as a puta-tive novel biomarker for MS

METHODS Classification of evidence We included pa-

tients with relapsing-remitting MS (RRMS) and patients with

clinically isolated syndrome (CIS) with a diagnosis according to

the 2005 revisions to the McDonald criteria11 and neurologic

disease controls who displayed no clinical or neuroradiologic

features of MS Furthermore noninflammatory neurologic disease

controls (NINDC) had no inflammatory lesions on MRI and no

signs of intrathecal inflammation as shown by the presence of any of

the following oligoclonal bands (OCBs) increased immunoglobulin

G (IgG) index or pleocytosis (higher than 23 upper normal limit

ie 10000 cellsmL) Inflammatory neurologic disease controls

(INDC) may or may not have inflammatory lesions on MRI

together with the presence of intrathecal inflammation as defined

above The inclusion of samples into 4 different diagnostic categories

(CIS RRMS NINDC and INDC) was based on obtaining

a comparable group size age female-to-male ratio and the period

of sampling among the 4 categories The miR-150 assays were

carried out on randomized samples in a blinded fashion and the

quantification analysis of miR-150 levels was performed by 2

people independently who were blind to the diagnostic status of

the samples

The objective of this study was to profile circulating miRNAs

in cell-free CSF in a large cohort of patients with MS and controls

to identify a novel biomarker for MS This study provides Class II

evidence

Patients During routine visits to the neurology clinic at Karo-

linska University Hospital patientsrsquo Expanded Disability Status

Scale (EDSS) score was determined by the treating neurologist

and CSF and blood samples were collected Patients were subdi-

vided into RRMS CIS INDC and NINDC MRI examinations

on 15T or 3T scanners were done according to clinical routine

Here we collected information on number of T2 and gadolinium-

enhancing lesions as judged from the original neuroradiologic

evaluation of scans performed within 66 months of sampling

For detailed patient demographics see table 1

Handling of samples The CSF samples were centrifuged

immediately after lumbar puncture at 440g for 10 minutes at

room temperature to separate cells and larger particles from the

CSF supernatant The blood samples were collected in EDTA

tubes and centrifuged at 1500g for 15 minutes Both the plasma

phase and the CSF supernatant were batched and stored at

280degC until use Methodologic details regarding measurements

of C-X-C motif chemokine 13 (CXCL13) matrix metallopepti-

dase 9 (MMP-9) osteopontin (OPN) and neurofilament light

chain (NFL) in CSF can be found in the original study12 Levels

of miRNA in CSF and plasma of patients with MS were deter-

mined at baseline and 12 months after open-label treatment with

natalizumab or fingolimod

Standard protocol approvals registrations and patientconsents CSF and blood samples were handled according to

consensus guidelines13 The study was approved by the regional

ethical committee (ethical permit 20092107-312) and written

informed consent was obtained from all patients

RNA isolation from cell-free CSF For miRNA TaqMan low

density arrays (TLDA) 4 CSF pools were created by combining

equal volumes of CSF from patients with CIS (n5 15) MS (n5

15) NINDC (n 5 13) and INDC (n 5 14) RNA was isolated

from 500 mL using the miRCURY RNA isolation kit for biofluids

(Exiqon Vedbaek Denmark) according to manufacturerrsquos proto-

col For normalization of sample-to-sample variation 2 fmol

synthetic Arabidopsis thaliana miRNA ath-miR159a 59-

UUUGGAUUGAAGGGAGCUCUA-39 (RNA oligonucleotide

Eurofins Genomics Ebersberg Germany) was spiked into each

CSF pool after addition of Lysis Solution BF

In addition to TLDA cards where CSF pools were used indi-

vidual CSF samples used in the profiling pools (n 5 57) and

validation cohort 1 (n 5 142) were subjected to total RNA iso-

lation using a standard TRIzol protocol where 700 mL of TRIzol

reagent (Invitrogen Life Technologies Carlsbad CA) was added

to 300 mL CSF sample For normalization of sample-to-sample

variation 2 fmol synthetic Arabidopsis thaliana miRNA ath-miR159a was spiked into each CSF sample after the addition of

TRIzol

RNA isolation for validation cohort 2 (n5 450) and natalizu-

mab- (n 5 20) and fingolimod-treated (n 5 17) patients was

performed on 300 mL CSF using the miRCURY RNA isolation

kit for biofluids For normalization of sample-to-sample variation

synthetic Caenorhabditis elegans miRNAs cel-miR-39 59-UCA

CCG GGU GUA AAU CAG CUU G-39 cel-miR-54 59-UACCCG UAA UCU UCA UAA UCC GAG-39 cel-miR-238 59-UUU GUA CUC CGA UGC CAU UCA GA-39 (RNA oligonu-

cleotides Integrated DNA Technologies Coralville IA) were

added as a mixture of 3 fmol per oligonucleotide to each denatured

sample All eluted RNA was immediately stored at 280degC

RNA isolation from cell-free plasma RNA isolation from

natalizumab- (n 5 17) and fingolimod-treated (n 5 17)

patients as well as a plasma cohort (n 5 156) was performed

from 100 mL plasma using the miRCURY RNA isolation

kit for biofluids according to manufacturerrsquos protocol For

normalization of sample-to-sample variation synthetic

Caenorhabditis elegans miRNAs cel-miR-39 cel-miR-54 and cel-miR-238 were added as a mixture of 15 fmol per oligonucleotide

to each denatured sample Eluted RNA was immediately stored

at 280degC

MiRNA profiling with TLDA MiRNA was reverse tran-

scribed using Megaplex RT Primers Human Pool Set v30

and TaqMan MicroRNA Reverse Transcription Kit (Applied Bi-

osystems Life Technologies) according to manufacturerrsquos instruc-

tions The reverse transcription (RT) products were preamplified





































lowest DDCt





















Tab

le1

Pat

ient

dem

ogra

phics

Poo

lValidat

ionco

hort

1Validat

ionco

hort

2Tre

atmen

tco

hort

Nat

alizum

ab

Tre

atmen

tco

hort

Fingolim

od

CIS

MS

NIN

DC

INDC

CIS

MS

NIN

DC

INDC

CIS

MS

NIN

DC

INDC

CSF

Plasm

aCSF

Plasm

a

Tot

alno

ofpat

ient

s15

15

13

14

34

43

34

31

96

120

119

95

20

17

17

Fem

alemale

132

123

94

113

241

0261

7241

0211

0712

5823

8823

7653

0127

125

125

Age

ymed

ian(ran

ge)

31

(20ndash61)

30

(22ndash56)

36

(36ndash55)

34

(21ndash58)

36

(21ndash52)

37

(18ndash61)

35

(21ndash63)

45

(13ndash64)

32

(16ndash60)

37

(18ndash73)

38

(21ndash72)

40

(21ndash71)

37

(23ndash53)

37

(23ndash53)

37(27ndash59)

EDSSm

edian(ran

ge)

1(0ndash3)

35

(15ndash6)

NA

NA

2(0ndash65)

25

(1ndash75)

NA

NA

1(0ndash6)

2(0ndash75)

1(0ndash6)

1(0ndash3)

38

(1ndash75)

45

(2ndash75)

2(1ndash65)

Disea

sedur

ations

(ons

et-to-sa

mplin

g)y

med

ian(ran

ge)

0(0ndash14)

4(0ndash9)

NA

NA

1(0ndash18)

7(0ndash40)

NA

NA

0(0ndash11)

6(0ndash46)

2(0ndash44)

2(0ndash56)

95

(1ndash26)

9(1ndash17)

13

(2ndash23)

Per

cent

sampleddur

ing

relapse

(n)

20

(15)

100

(15)

NA

NA

20

(34)

26

(43)

NA

NA

26

(96)

31

(120)

NA

NA

15

(20)

12

(17)

6(17)

OCB-pos

itive(n)

86

(14)

93

(14)

0(12)

0(6)

45

(31)

88

(43)

0(31)

9(22)

71

(49)

82

(105)

0(64)

13

(31)

85

(20)

88

(17)

88

(17)

CSFmon

onuc

lear

cells

med

ian(ran

ge)

8(3ndash36)

7(1ndash90)

2(0ndash5)

1(0ndash17)

25

(0ndash92)

6(0ndash40)

2(0ndash7)

2(0ndash15)

4(0ndash36)

4(0ndash40)

1(0ndash11)

2(0ndash433)

6(1ndash34)

55

(1ndash34)

2(0ndash14)

Per

cent

conv

erte

dCIS

60

NA

NA

NA

NA

NA

NA

NA

63

NA

NA

NA

NA

NA

NA

Abb

reviations

CIS

5clinically

isolated

synd

rome

EDSS

5Exp

ande

dDisab

ility

StatusSca

leIN

DC

5inflam

matoryne

urolog

icdise

aseco

ntrolsMS

5multiplesc

lerosis

NA

5no

tap

plicab

leNIN

DC

5no

n-inflam

matoryne

urolog

icdise

aseco

ntrolsO

CB

5oligoc

lona

lban

ds

The(n)ind

icates

numbe

rof

samples

forwhich

theinform

ationwas

available


























MRIlesions EDSS


miR-150 vs cel

No 181 170 180 142 180 179 164 125 162 104 162 162

R 2018 033a 033a 005 2002 2003 2001 044a 031a 026ab 007 014

p Value 002 00001a 00001a 053 080 064 092 00001a 00001a 0008a 040 008

miR-150 vs 204

No 181 170 180 142 180 179 164 125 162 104 162 162

R 2022a 032a 046a 002 2007 2012 2007 060a 054a 020 015 021a

p Value 0002a 00001a 00001a 078 034 012 037 00001a 00001a 004 006 0007a

CXCL13

No 129 120 128 106 128 127 114 129 124 91 124 124

R 2037a 057a 064a 023 001 2004 004 1 069a 025 033a 043a

p Value 00001a 00001a 00001a 002 092 066 070 00001a 002 00002a 00001a

MMP-9

No 168 157 167 135 168 166 151 168 110 168 168

R 2031a 050a 049a 012 2020a 2021ab 2016 1 007 2001 007

p Value 00001a 00001a 00001a 018 0009a 0006a 006 049 093 040

OPN

No 110 102 110 82 110 109 104 110 110 110

R 019 019 022 032ac 021 020 026a 1 025ac 022

p Value 005 005 002 0004a 003 004 0007a 0009a 002

NFL

No 168 157 167 135 168 166 151 168 168

R 000 2000 013 028a 027a 023a 023a 1 097a

p Value 098 098 009 0001a 00005a 0003a 0005a 00001a

NFLadj

No 168 157 167 135 168 166 151 168

R 2018 006 024a 029a 024a 017 016 1

p Value 002 043 0002a 00007a 0002a 003 005





































manuscript




































275364ndash381























































One 20149e89237











980ndash986









e0135886






One 20138e78762







201510e0126423



















267ndash276











7053ndash7062







mun 20112282



201039133ndash144






















Reprints






































lowest DDCt





















Tab

le1

Pat

ient

dem

ogra

phics

Poo

lValidat

ionco

hort

1Validat

ionco

hort

2Tre

atmen

tco

hort

Nat

alizum

ab

Tre

atmen

tco

hort

Fingolim

od

CIS

MS

NIN

DC

INDC

CIS

MS

NIN

DC

INDC

CIS

MS

NIN

DC

INDC

CSF

Plasm

aCSF

Plasm

a

Tot

alno

ofpat

ient

s15

15

13

14

34

43

34

31

96

120

119

95

20

17

17

Fem

alemale

132

123

94

113

241

0261

7241

0211

0712

5823

8823

7653

0127

125

125

Age

ymed

ian(ran

ge)

31

(20ndash61)

30

(22ndash56)

36

(36ndash55)

34

(21ndash58)

36

(21ndash52)

37

(18ndash61)

35

(21ndash63)

45

(13ndash64)

32

(16ndash60)

37

(18ndash73)

38

(21ndash72)

40

(21ndash71)

37

(23ndash53)

37

(23ndash53)

37(27ndash59)

EDSSm

edian(ran

ge)

1(0ndash3)

35

(15ndash6)

NA

NA

2(0ndash65)

25

(1ndash75)

NA

NA

1(0ndash6)

2(0ndash75)

1(0ndash6)

1(0ndash3)

38

(1ndash75)

45

(2ndash75)

2(1ndash65)

Disea

sedur

ations

(ons

et-to-sa

mplin

g)y

med

ian(ran

ge)

0(0ndash14)

4(0ndash9)

NA

NA

1(0ndash18)

7(0ndash40)

NA

NA

0(0ndash11)

6(0ndash46)

2(0ndash44)

2(0ndash56)

95

(1ndash26)

9(1ndash17)

13

(2ndash23)

Per

cent

sampleddur

ing

relapse

(n)

20

(15)

100

(15)

NA

NA

20

(34)

26

(43)

NA

NA

26

(96)

31

(120)

NA

NA

15

(20)

12

(17)

6(17)

OCB-pos

itive(n)

86

(14)

93

(14)

0(12)

0(6)

45

(31)

88

(43)

0(31)

9(22)

71

(49)

82

(105)

0(64)

13

(31)

85

(20)

88

(17)

88

(17)

CSFmon

onuc

lear

cells

med

ian(ran

ge)

8(3ndash36)

7(1ndash90)

2(0ndash5)

1(0ndash17)

25

(0ndash92)

6(0ndash40)

2(0ndash7)

2(0ndash15)

4(0ndash36)

4(0ndash40)

1(0ndash11)

2(0ndash433)

6(1ndash34)

55

(1ndash34)

2(0ndash14)

Per

cent

conv

erte

dCIS

60

NA

NA

NA

NA

NA

NA

NA

63

NA

NA

NA

NA

NA

NA

Abb

reviations

CIS

5clinically

isolated

synd

rome

EDSS

5Exp

ande

dDisab

ility

StatusSca

leIN

DC

5inflam

matoryne

urolog

icdise

aseco

ntrolsMS

5multiplesc

lerosis

NA

5no

tap

plicab

leNIN

DC

5no

n-inflam

matoryne

urolog

icdise

aseco

ntrolsO

CB

5oligoc

lona

lban

ds

The(n)ind

icates

numbe

rof

samples

forwhich

theinform

ationwas

available


























MRIlesions EDSS


miR-150 vs cel

No 181 170 180 142 180 179 164 125 162 104 162 162

R 2018 033a 033a 005 2002 2003 2001 044a 031a 026ab 007 014

p Value 002 00001a 00001a 053 080 064 092 00001a 00001a 0008a 040 008

miR-150 vs 204

No 181 170 180 142 180 179 164 125 162 104 162 162

R 2022a 032a 046a 002 2007 2012 2007 060a 054a 020 015 021a

p Value 0002a 00001a 00001a 078 034 012 037 00001a 00001a 004 006 0007a

CXCL13

No 129 120 128 106 128 127 114 129 124 91 124 124

R 2037a 057a 064a 023 001 2004 004 1 069a 025 033a 043a

p Value 00001a 00001a 00001a 002 092 066 070 00001a 002 00002a 00001a

MMP-9

No 168 157 167 135 168 166 151 168 110 168 168

R 2031a 050a 049a 012 2020a 2021ab 2016 1 007 2001 007

p Value 00001a 00001a 00001a 018 0009a 0006a 006 049 093 040

OPN

No 110 102 110 82 110 109 104 110 110 110

R 019 019 022 032ac 021 020 026a 1 025ac 022

p Value 005 005 002 0004a 003 004 0007a 0009a 002

NFL

No 168 157 167 135 168 166 151 168 168

R 000 2000 013 028a 027a 023a 023a 1 097a

p Value 098 098 009 0001a 00005a 0003a 0005a 00001a

NFLadj

No 168 157 167 135 168 166 151 168

R 2018 006 024a 029a 024a 017 016 1

p Value 002 043 0002a 00007a 0002a 003 005





































manuscript




































275364ndash381























































One 20149e89237











980ndash986









e0135886






One 20138e78762







201510e0126423



















267ndash276











7053ndash7062







mun 20112282



201039133ndash144






















Reprints



























MRIlesions EDSS


miR-150 vs cel

No 181 170 180 142 180 179 164 125 162 104 162 162

R 2018 033a 033a 005 2002 2003 2001 044a 031a 026ab 007 014

p Value 002 00001a 00001a 053 080 064 092 00001a 00001a 0008a 040 008

miR-150 vs 204

No 181 170 180 142 180 179 164 125 162 104 162 162

R 2022a 032a 046a 002 2007 2012 2007 060a 054a 020 015 021a

p Value 0002a 00001a 00001a 078 034 012 037 00001a 00001a 004 006 0007a

CXCL13

No 129 120 128 106 128 127 114 129 124 91 124 124

R 2037a 057a 064a 023 001 2004 004 1 069a 025 033a 043a

p Value 00001a 00001a 00001a 002 092 066 070 00001a 002 00002a 00001a

MMP-9

No 168 157 167 135 168 166 151 168 110 168 168

R 2031a 050a 049a 012 2020a 2021ab 2016 1 007 2001 007

p Value 00001a 00001a 00001a 018 0009a 0006a 006 049 093 040

OPN

No 110 102 110 82 110 109 104 110 110 110

R 019 019 022 032ac 021 020 026a 1 025ac 022

p Value 005 005 002 0004a 003 004 0007a 0009a 002

NFL

No 168 157 167 135 168 166 151 168 168

R 000 2000 013 028a 027a 023a 023a 1 097a

p Value 098 098 009 0001a 00005a 0003a 0005a 00001a

NFLadj

No 168 157 167 135 168 166 151 168

R 2018 006 024a 029a 024a 017 016 1

p Value 002 043 0002a 00007a 0002a 003 005





































manuscript




































275364ndash381























































One 20149e89237











980ndash986









e0135886






One 20138e78762







201510e0126423



















267ndash276











7053ndash7062







mun 20112282



201039133ndash144






















Reprints





































manuscript




































275364ndash381























































One 20149e89237











980ndash986









e0135886






One 20138e78762







201510e0126423



















267ndash276











7053ndash7062







mun 20112282



201039133ndash144






















Reprints

















































One 20149e89237











980ndash986









e0135886






One 20138e78762







201510e0126423



















267ndash276











7053ndash7062







mun 20112282



201039133ndash144






















Reprints




















Reprints




Circulating miR-150 in CSF is a novel candidate biomarker for … · candidate biomarker for...

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Transcript of Circulating miR-150 in CSF is a novel candidate biomarker for … · candidate biomarker for...