an immunochip study of multiple sclerosis risk
DESCRIPTION
An ImmunoChip study of multiple sclerosis riskin African AmericansTRANSCRIPT
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An ImmunoChip study of multiple sclerosis riskin African Americans
Noriko Isobe,1,2 Lohith Madireddy,1 Pouya Khankhanian,1 Takuya Matsushita,1,3
Stacy J. Caillier,1 Jayaji M. More,1 Pierre-Antoine Gourraud,1 Jacob L. McCauley,4
Ashley H. Beecham,4 International Multiple Sclerosis Genetics Consortium, Laura Piccio,5
Joseph Herbert,6 Omar Khan,7 Jeffrey Cohen,8 Lael Stone,8 Adam Santaniello,1
Bruce A. C. Cree,1 Suna Onengut-Gumuscu,9 Stephen S. Rich,9 Stephen L. Hauser,1
Stephen Sawcer10,* and Jorge R. Oksenberg1,*
*These authors contributed equally to this work.
The aims of this study were: (i) to determine to what degree multiple sclerosis-associated loci discovered in European populations
also inuence susceptibility in African Americans; (ii) to assess the extent to which the unique linkage disequilibrium patterns in
African Americans can contribute to localizing the functionally relevant regions or genes; and (iii) to search for novel African
American multiple sclerosis-associated loci. Using the ImmunoChip custom array we genotyped 803 African American cases with
multiple sclerosis and 1516 African American control subjects at 130 135 autosomal single nucleotide polymorphisms. We con-
ducted association analysis with rigorous adjustments for population stratication and admixture. Of the 110 non-major histo-
compatibility complex multiple sclerosis-associated variants identied in Europeans, 96 passed stringent quality control in our
African American data set and of these, 470% (69) showed over-representation of the same allele amongst cases, including 21with nominally signicant evidence for association (one-tailed test P5 0.05). At a further eight loci we found nominally signicantassociation with an alternate correlated risk-tagging single nucleotide polymorphism from the same region. Outside the regions
known to be associated in Europeans, we found seven potentially associated novel candidate multiple sclerosis variants (P5 104),one of which (rs2702180) also showed nominally signicant evidence for association (one-tailed test P = 0.034) in an independent
second cohort of 620 African American cases and 1565 control subjects. However, none of these novel associations reached
genome-wide signicance (combined P = 6.3 105). Our data demonstrate substantial overlap between African American andEuropean multiple sclerosis variants, indicating common genetic contributions to multiple sclerosis risk.
1 Department of Neurology, School of Medicine, University of California, San Francisco, CA 94158, USA2 Division of Neurology, Department of Internal Medicine, Saga University Faculty of Medicine, Saga, Saga 849-8501, Japan3 Department of Neurological Therapeutics, Neurological Institute, Graduate School of Medical Sciences, Kyushu University,
Fukuoka, Fukuoka 812-8582, Japan4 John P. Hussman Institute for Human Genomics and The Dr John T Macdonald Foundation Department of Human Genetics,
University of Miami, Miller School of Medicine, Miami, FL 33136, USA5 Department of Neurology, Washington University School of Medicine, St. Louis, MO 63108, USA6 Department of Neurology, New York University School of Medicine, New York, NY 10016, USA7 Multiple Sclerosis Centre and The Sastry Foundation Advanced Imaging Laboratory, Department of Neurology, Wayne State
University School of Medicine, Detroit, MI 48201, USA8 Mellen Centre for Multiple Sclerosis Treatment and Research, Cleveland Clinic, Cleveland, OH 44195, USA9 Centre for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA10 Department of Clinical Neurosciences, Cambridge Biomedical Campus, Hills Road, Cambridge CB2 0QQ, UK
doi:10.1093/brain/awv078 BRAIN 2015: 138; 15181530 | 1518
Received November 20, 2014. Revised January 5, 2015. Accepted January 26, 2015. Advance Access publication March 28, 2015
The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved.For Permissions, please email: [email protected]
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Correspondence to: Jorge R. Oksenberg, PhD,
Department of Neurology, School of Medicine,
University of California,
San Francisco,
675 Nelson Rising Lane,
Room 215C,
San Francisco,
CA 94158, USA
E-mail: [email protected]
Keywords: multiple sclerosis; African Americans; ImmunoChip; linkage disequilibrium
Abbreviations: GWAS = genome-wide association study; IMSGC = International Multiple Sclerosis Genetics Consortium;MHC = major histocompatibility complex; SNP = single nucleotide polymorphism; WTCCC2 = Wellcome Trust Case ControlConsortium 2
IntroductionMultiple sclerosis is a chronic, inammatory disease of the
CNS and a common cause of neurological disability in
young adults (Hauser and Goodin, 2012). Its modest her-
itability reects complex polygenic effects and, most likely,
gene-environment interactions [Simon et al., 2011;
International Multiple Sclerosis Genetics Consortium
(IMSGC), 2013a; Sawcer et al., 2014]. The results from
genome-wide association studies (GWAS) have claried im-
portant aspects of multiple sclerosis pathogenesis and pro-
vided strong empirical support for a model of inheritance
driven primarily by allelic variants that are relatively
common in the general population [Oksenberg and
Baranzini, 2010; IMSGC and Wellcome Trust Case
Control Consortium 2 (WTCCC2), 2011]. The strongest
susceptibility signal genome-wide maps to HLA-DRB1 in
the class II region of the major histocompatibility complex
(MHC, 6p21.3) and explains up to 10.5% of the genetic
variance underlying risk. The HLA association implies that
mechanistically, multiple sclerosis clusters with other anti-
gen-specic autoimmune diseases, a hypothesis supported
by the observation that the non-MHC associated variants
appear to locate predominantly in or near genes inuencing
the function of the adaptive immune system (IMSGC and
WTCCC2, 2011). Interestingly, some of the non-MHC al-
lelic variants associated with multiple sclerosis have also
emerged in GWAS of other autoimmune diseases (IMSGC
and WTCCC2, 2011; Cotsapas et al., 2011), suggesting
that common underlying risk mechanisms might exist
across multiple immune-related conditions. To better
describe this overlap and rene the regions of interest in
susceptibility loci, a mega-consortium was established to
conduct cost-effective candidate loci association studies
across multiple autoimmune diseases using a common,
high-coverage single nucleotide polymorphisms (SNPs)
array known as the ImmunoChip (Cortes and Brown,
2011). The chip was designed in 2010 and 207728 vari-
ants were considered for inclusion, of which 196 524
passed manufacturing quality control (192 402 autosomal,
1595 X-linked, 1735 Y-linked, 791 pseudoautosomal and
one mitochondrial). The multiple sclerosis input to the con-
tent came from two sources: an early analysis of a well-
powered GWAS (IMSGC and WTCCC2, 2011) and a
meta-analysis of previously published smaller GWAS
(Patsopoulos et al., 2011).
Typing the ImmunoChip in a new independent data set
identied 48 novel multiple sclerosis susceptibility variants
with genome-wide signicance (IMSGC, 2013b). These re-
sults considerably enhanced the roster of validated risk loci
and demonstrated the discovery power of this array that
has been similarly effective in other autoimmune diseases
(Trynka et al., 2011; Cooper et al., 2012; Eyre et al., 2012;
Jostins et al., 2012; Juran et al., 2012; Liu et al., 2012;
Tsoi et al., 2012; Hinks et al., 2013). However, the utility
of this platform in non-Europeans remains to be addressed.
In addition, consistent with their longer evolutionary his-
tory, populations of African origin are known to have, on
average, characteristically smaller blocks of linkage disequi-
librium compared to populations with European ancestry
(Tishkoff and Kidd, 2004), implying that the study of
populations of African origin could help to narrow the re-
gions of interest and assist in identifying causative variants
(Buyske et al., 2012; Gong et al., 2013).
Notwithstanding difculties in surveillance, multiple
sclerosis is almost non-existent in black Africans and
early estimates suggested that the disease was signicantly
less prevalent in African Americans than in European
Americans (relative risk of 0.64; Wallin et al., 2004).
However, contemporary studies are challenging the long-
held belief that African Americans are at a reduced risk
for developing multiple sclerosis (Wallin et al., 2012;
Langer-Gould et al., 2013). Furthermore, compared with
whites, African Americans are more likely to have a more
severe disease course, which at least in part appears to be
genetically determined (Buchanan et al., 2004; Cree et al.,
2004, 2009; Boster et al., 2009; Kimbrough et al., 2014).
Here, we applied the ImmunoChip to a well-curated
African American multiple sclerosis data set to investigate:
(i) whether European multiple sclerosis-associated variants
ImmunoChip in African Americans with MS BRAIN 2015: 138; 15181530 | 1519
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are also associated with the disease in African Americans;
(ii) whether the smaller haplotype blocks, characteristic of
African American genomes, can contribute to better map-
ping of the functionally relevant variants driving the asso-
ciation; and (iii) whether the array can identify novel
multiple sclerosis-associated loci in African American
patients.
Materials and methods
Patients and control subjects
The core screening data set consists of 842 de-identied DNAsamples from African American cases and 498 AfricanAmerican controls. All multiple sclerosis subjects met estab-lished diagnostic criteria (McDonald et al., 2001; Polmanet al., 2011). Ascertainment protocols and clinical and demo-graphic characteristics have been summarized elsewhere (Creeet al., 2004; Oksenberg et al., 2004). All study participants areself-reported African Americans. Additionally, data from 1114African American control subjects were provided by theInternational Consortium on the Genetics of Systemic LupusErythematosus (SLEGEN), totalling 842 cases and 1612 con-trols. The University of California at San FranciscoInstitutional Review Board approved this study.
SNP genotyping and quality control
SNP genotyping was conducted using the ImmunoChip, anIllumina Innium HD custom array at the Wellcome TrustSanger Institute, Hinxton, Cambridge, UK for the cases andat the Centre for Public Health Genomics, University ofVirginia, Charlottesville, VA, USA for the controls. Standardquality control measures were implemented using PLINKv1.07 (Purcell et al., 2007). SNPs with missing rates higherthan 2%, Hardy-Weinberg proportion test P5105 in con-trols and P5108 in cases, and distinct missing proportionbetween cases and controls with P5 103 were excluded. Forthe further analysis, 130 248 autosomal SNPs remained,including 96 of 110 SNPs known to be associated inEuropeans (IMSGC, 2013b). Samples were excluded for miss-ing genotyping rates exceeding 2%, extreme autosomal hetero-zygosity of 43 standard deviations (SD), or excessive IdentityBy Descent (IBD) with PI_HAT 40.20.
Population stratification
Principal component (PC) analyses were used to assess ances-try and control for the effects of population stratication.Principal component analysis was conducted using prunedautosomal non-MHC SNPs with minor allele frequency41% and pairwise r25 0.1 with a window size of 100SNPs (25 408 SNPs). The scree plot indicated that PC1 ex-plained the vast majority of the variance in the AfricanAmerican data set (Supplementary Fig. 1A). According to theplot, PC1 were used to remove two outlier samples with thevalues outside 6 SD and all following association analyseswere conducted using PC1 as a covariate. PC1 values werehighly correlated with the previously reported percentage ofAfrican ancestry (r = 0.99, P52.2 1016) (Reich et al.,
2005; Isobe et al., 2013). When the PC1 components of indi-vidual samples were compared with each other, the controlsamples from SLEGEN had higher PC1 values compared tothe UCSF cases and controls (P = 2.53 1027 and1.77 1016, respectively), suggesting the proximity ofSLEGEN controls to African ancestry (Supplementary Fig.1B). Thus, to eliminate association signals derived from thedifferent population admixture levels between the two controlgroups, association was analysed between the two with PC1 asa covariate, which identied 113 SNPs with P-values 5103
to be removed. Finally, 130 135 autosomal SNPs remained forthe following analysis. Another principal component analysiswas conducted including samples from the 1000 GenomeProject (The 1000 Genomes Project Consortium, 2010) as areference, with commonly available autosomal SNPs prunedwith the same criteria as above (24 994 SNPs). From thisprincipal component analysis, an additional 22 sampleslocated far from the relevant reference populations wereremoved (Fig. 1). Ultimately, 803 African American multiplesclerosis cases and 1516 healthy African American controlsubjects remained for further analysis. Principal componentanalyses were performed using the R package SNPRelate(Zheng et al., 2012).
Association analysis
Following quality control analyses, association tests were con-ducted assuming the additive effect of the allele for the affect-ation status with PC1 as a covariate to control for populationstratication and admixture. First, the replication status of 96European multiple sclerosis SNPs (IMSGC, 2013b) was eval-uated using one-tailed tests. For each multiple sclerosis variant,the Cochrane Heterogeneity Q Test was also performed to testeffect size differences between African Americans andEuropeans. Additionally, SNPs with association P-values5104 locating outside 2Mb (1Mb centromeric and 1Mbtelomeric) anking the European multiple sclerosis-associatedSNPs were nominated as candidates for novel multiple scler-osis-associated variants in African Americans. All associationtests for genotyped SNPs were conducted using PLINK (v1.07)(Purcell et al., 2007). Power calculations were performed usingBioconductors GeneticsDesign package version 1.28.0(Warnes et al., 2010).
Fine mapping with imputation
For multiple sclerosis SNPs, regardless of evidence of replicationin African Americans, we assessed whether there was a morestrongly associated risk-tagging SNP in the region anking themultiple sclerosis SNP by testing for association amongst thegenotyped SNPs from these regions, including those assessableby imputation. The regions of multiple sclerosis SNPs weredened as the range of chromosomal positions where SNPsin linkage disequilibrium around the multiple sclerosisSNPs with r240.5 locate in the European populations of the1000 Genome Project. Imputation was performed usingIMPUTE2 (v2.3.0) (Howie et al., 2009) and the 1000Genomes Phase 1 integrated haplotypes (released in September2013) were used as a reference panel. In addition to thepreviously conducted quality control measures, those AT/GCSNPs with failed alignment were removed. Missing genotypesfor the genotyped SNPs were not imputed. To increase the
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imputation accuracy we did not pre-phase genotypes and thenumber of Markov chain Monte Carlo iteration (-iter) was
increased to 60 with burnin 20. Association tests were con-
ducted with the frequentist test using SNPTEST (v2.5b) assum-ing an additive effect of each SNP (Marchini and Howie,
2010). Similar to the analysis in the genotyped SNPs, the PC1
component was included as a covariate in the analysis. SNPswere removed when they had poor imputation accuracy with
the INFO score obtained from IMPUTE2 lower than 0.7,
minor allele frequency 51%, or a Hardy-WeinbergEquilibrium test violation (P5105 in controls andP5 108 in cases). Regions were also considered replicatedwhen a neighbouring SNP had an association with false dis-
covery rate (FDR) P5 0.05 corrected with P-values of all theSNPs, both genotyped and imputed, within the region. To cal-
culate linkage disequilibrium parameters between the original
European multiple sclerosis SNP and the optimal risk-taggingSNP of African Americans, we used the 1000 Genome Project
population data set (The 1000 Genomes Project Consortium,
2010) for Europeans and our case-control data set for African
Americans. GTOOL (v0.7.5) (Freeman and Marchini, 2007)was used to convert post-imputed genetic data to PLINK-
format data to be ready to calculate linkage disequilibrium in
PLINK. Imputation was also performed for the linkage disequi-librium region of the candidate novel multiple sclerosis variants
using a maximum range of positions where proxy SNPs
(r24 0.5 in African Americans) of the candidate SNPs locateto capture the possible causative variants. ANNOVAR
(Wang et al., 2010), SNPnexus (Dayem Ullah et al., 2013),and RegulomeDB (Boyle et al., 2012) were used to annotateobtained variants. We plotted the association test results
using LocusZoom (Pruim et al., 2010) with neededmodications.
Replication study of unreportedmultiple sclerosis variants
For the candidate multiple sclerosis loci previously unreportedin Europeans, a replication study was conducted on an inde-pendent African American group consisting of 620 multiplesclerosis cases and 1565 controls by genotyping the topSNPs after imputation in the region of interest. SNP genotyp-ing was completed in the replication data set using predesignedand custom TaqMan SNP Genotyping Assays. TaqMan
SNP genotyping assays were conducted in 384-well plates onan ABI 7900HT Sequence Detection System using SDS 2.3software. Association P-values were provided with one-tailedtest. We also performed meta-analysis under a xed-effectsmodel with effect sizes and standards errors from the AfricanAmerican ImmunoChip (discovery) data set and the replicationstudy. Here a SNP was considered to have replicated when thereplication P5 0.05 (one-tailed test) and the combined P-valueof meta-analysis is more signicant than the discovery P-value.For the replication study, no adjustment of population admix-ture was conducted.
Results
Replication study of the multiplesclerosis-associated SNPs innon-MHC regions
We screened 130 135 autosomal SNPs in 803 African
American multiple sclerosis cases and 1516 African
American control subjects. Figure 2 shows a Circos plot
summarizing the results from this screen; as anticipated,
the strongest association was observed in the MHC
region on chromosome 6p21.3 (P = 2.75 108). InEuropeans 110 SNPs from 103 discrete loci outside the
MHC region have been established as risk variants in mul-
tiple sclerosis (IMSGC, 2013b); in our African American
screen, results passing stringent quality control were avail-
able for 96 of these SNPs (including rs3190930 a proxy
SNP for rs802734, Supplementary Table 1). Amongst these
96 we found that 470% (69/96) had the same allele over-represented in cases as in European multiple sclerosis cases,
a highly signicant excess of concordance (one-tailed bino-
mial test P = 1.07 105). For 21 of these 69 the excessfrequency in cases was nominally signicant (one-tailed test
P5 0.05) (Table 1); for all of these the effect sizes inAfrican Americans were statistically indistinguishable from
those observed in Europeans (heterogeneity test P40.05,Supplementary Table 1). Even including unreplicated mul-
tiple sclerosis SNP, the obtained effect sizes of multiple
sclerosis variants in African Americans were generally cor-
related with those in Europeans (Supplementary Fig. 2). To
estimate the level of concordance that might be expected if
effects were the same in African Americans as in
Europeans, we estimated for each of the 96 SNPs the
power of a study with 803 cases and 1516 control subjects
Figure 1 Principal component analysis of the African
American Immunochip data set with reference to samples
from the 1000 Genome Project. African American (AfAm)
case/control samples are shown as + and reference samples from
the 1000 Genome Project are shown as closed circles. YRI and
LWK = Africans; ASW = African Americans; CEU, TSI, FIN, GBR
and IBS = Europeans; MXL, PUR, CLM = Central-South Americans;
CHB, CHS and JPN = Asians.
ImmunoChip in African Americans with MS BRAIN 2015: 138; 15181530 | 1521
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to identify nominally signicant association (one-tailed test
P50.05 or half the power to observe two-tailed testP50.1), assuming effect sizes equivalent to those seen inthe European screen (IMSGC, 2013b) and the risk allele
frequencies observed in our African American control
population (Supplementary Table 1). Across the 96 variants
we found that the average power was 18.6%, with values
ranging from 5.5% (at rs2028597) to 49.9% (at
rs6677309). Based on this average value we would antici-
pate seeing nominally signicant association (one-tailed test
P5 0.05) at between 12 and 24 SNPs with the same riskallele as in Europeans. Our observation of 21 such SNPs is
thus entirely consistent with these variants exerting equiva-
lent effect in African Americans and Europeans.
Figure 2 Circos plot of ImmunoChip in African Americans. The outermost track shows the autosomal chromosomes. The second track
indicates the genes closest to the non-MHC multiple sclerosis-associated variants. Gene names of replicated loci in African Americans with
identical SNPs as Europeans are shown in bold black, replicated loci with alternate variants are shown in bold blue, and unreplicated loci are
shown in grey. The replicated novel multiple sclerosis locus in African Americans is indicated in bold red. The innermost track indicates log10(P)
(two-tailed test) of association tests for each ImmunoChip SNP from African Americans (dark blue) and Europeans (light blue). The range of y-axis
is 08, excluding the peaks of Europeans with higher significance. The dark red line in the middle of the plot represents log10(P) = 4.
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Tab
le1
Rep
licate
d21
SN
Ps
inA
fric
an
Am
eri
can
so
ut
of
96
no
n-M
HC
mu
ltip
lesc
lero
sis
susc
ep
tib
ilit
yvari
an
tso
fE
uro
pean
s
Ch
rrs
IDP
osi
tio
nG
en
ea
Fu
ncti
on
RA
Eu
rop
ean
sbA
fric
an
Am
eri
can
sh
et.P
dP
ow
er
RA
FO
R(9
5%
CI)
PR
AF
RA
FO
R(9
5%
CI)
Pc
(co
nt.
)(c
ase
s)(c
on
t.)
(on
e-t
ailed
)
1rs
6677309
117080166
CD58
Intr
onic
A0.8
79
1.3
4(1
.271.4
1)
1.5
10
28
0.5
47
0.4
71
1.2
3(1
.091.3
9)
4.7
10
04
2.2
10
01
0.4
99
16
rs12927355
11194771
CLEC16A
Intr
onic
G0.6
78
1.2
1(1
.171.2
6)
8.2
10
27
0.7
87
0.7
47
1.2
8(1
.101.4
8)
5.3
10
04
4.8
10
01
0.4
21
19
rs11554159
18285944
IFI30
Exonic
G0.7
30
1.1
5(1
.111.2
0)
2.6
10
13
0.7
95
0.7
55
1.2
7(1
.091.4
7)
8.7
10
04
2.1
10
01
0.3
07
5rs
71624119
55440730
ANKRD55
Intr
onic
G0.7
55
1.1
2(1
.081.1
7)
2.7
10
09
0.9
43
0.9
35
1.4
0(1
.081.8
2)
6.1
10
03
1.0
10
01
0.1
16
7rs
917116
28172739
JAZF1
Intr
onic
C0.2
05
1.1
2(1
.071.1
6)
2.1
10
08
0.7
15
0.7
02
1.2
0(1
.041.3
7)
6.2
10
03
3.8
10
01
0.2
56
3rs
1920296
121543577
IQCB1
Intr
onic
C0.6
44
1.1
4(1
.111.1
8)
6.8
10
15
0.7
28
0.7
00
1.1
9(1
.041.3
6)
7.1
10
03
5.7
10
01
0.3
07
1rs
2050568
157770241
FCRL1
Intr
onic
G0.5
34
1.0
8(1
.051.1
2)
1.3
10
06
0.2
02
0.1
56
1.2
1(1
.031.4
2)
1.1
10
02
1.8
10
01
0.1
20
12
rs1800693
6440009
TNFRSF1A
Intr
onic
G0.3
98
1.1
4(1
.111.1
8)
6.9
10
16
0.3
99
0.3
62
1.1
6(1
.021.3
1)
1.1
10
02
8.2
10
01
0.3
29
10
rs2688608
75658349
(C10orf55)
Inte
rgenic
A0.5
49
1.0
7(1
.031.1
0)
6.4
10
05
0.3
07
0.2
54
1.1
7(1
.021.3
4)
1.3
10
02
2.2
10
01
0.1
26
10
rs2104286
6099045
IL2RA
Intr
onic
A0.7
22
1.2
1(1
.161.2
6)
7.6
10
23
0.9
39
0.9
33
1.3
3(1
.031.7
1)
1.4
10
02
4.8
10
01
0.2
23
18
rs7238078
56384192
MALT1
Intr
onic
A0.7
70
1.0
5(1
.021.1
0)
6.3
10
03
0.7
77
0.7
43
1.1
7(1
.021.3
5)
1.5
10
02
1.4
10
01
0.0
90
20
rs2248359
52791518
(CYP2
4A1)
Inte
rgenic
G0.5
99
1.0
7(1
.031.1
0)
9.8
10
05
0.3
99
0.3
54
1.1
5(1
.011.3
0)
1.7
10
02
2.9
10
01
0.1
40
3rs
2028597
105558837
CBLB
Intr
onic
G0.9
20
1.0
4(0
.981.1
1)
1.8
10
01
0.9
72
0.9
62
1.4
6(1
.022.0
8)
1.9
10
02
6.6
10
02
0.0
55
7rs
201847125
50325567
(IKZF1
)In
terg
enic
G0.6
95
1.1
1(1
.071.1
5)
2.9
10
08
0.9
01
0.8
93
1.2
4(1
.011.5
3)
1.9
10
02
2.9
10
01
0.1
38
1rs
7552544
101240893
(VCAM1)
Inte
rgenic
A0.5
58
1.0
8(1
.051.1
2)
3.7
10
06
0.8
10
0.8
00
1.1
8(1
.011.3
8)
2.0
10
02
2.8
10
01
0.1
31
3rs
2255214
121770539
(CD86)
Inte
rgenic
C0.5
18
1.1
1(1
.081.1
5)
1.7
10
10
0.7
26
0.7
12
1.1
5(1
.001.3
2)
2.4
10
02
6.5
10
01
0.2
25
7rs
1843938
3113034
(CARD11)
Inte
rgenic
A0.4
38
1.0
8(1
.051.1
2)
2.2
10
06
0.4
35
0.4
11
1.1
3(1
.001.2
9)
2.8
10
02
4.8
10
01
0.1
71
5rs
4976646
176788570
RGS1
4In
tronic
G0.3
40
1.1
3(1
.091.1
7)
1.0
10
12
0.5
58
0.5
37
1.1
3(1
.001.2
7)
3.0
10
02
9.6
10
01
0.3
14
11
rs7120737
47702395
AGBL2
Intr
onic
G0.1
45
1.1
3(1
.081.1
8)
7.6
10
08
0.2
86
0.2
66
1.1
4(0
.991.3
0)
3.2
10
02
9.3
10
01
0.2
75
3rs
9282641
121796768
CD86
Utr
5G
0.9
19
1.1
2(1
.051.1
9)
5.9
10
04
0.9
66
0.9
56
1.3
5(0
.971.8
8)
3.7
10
02
2.8
10
01
0.0
96
19
rs34536443
10463118
TYK2
Exonic
C0.9
51
1.2
8(1
.181.4
0)
1.2
10
08
0.9
96
0.9
94
2.1
2(0
.875.1
8)
4.9
10
02
2.7
10
01
0.0
80
Posi
tion
isbas
ed
on
hum
ange
nom
e19
and
dbSN
P137.
aW
hen
SNPs
loca
tein
terg
enic
,th
ecl
ose
stge
nes
are
show
nin
bra
ckets
.bR
esu
lts
of
Euro
pean
sar
eori
ginat
ed
from
IMSG
C,2013b.
cSN
Ps
with
asso
ciat
ionP-
valu
es5
0.0
5(o
ne-t
aile
dte
st)
were
show
n.
dC
och
rane
Hete
roge
neity
Qte
st.
AA
=A
fric
anA
meri
cans;
Chr
=ch
oro
moso
me;C
I=
confidence
inte
rval
;co
nt.
=co
ntr
ols
;het.
=hete
roge
neity;
RA
=ri
skal
lele
;R
AF
=ri
skal
lele
frequency
.
ImmunoChip in African Americans with MS BRAIN 2015: 138; 15181530 | 1523
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Unsurprisingly, the two SNPs with the most signicant as-
sociation in the African Americans were those with the
strongest effects in Europeans, rs6677309 (CD58) andrs12927355 (CLEC16A).
Among the 21 replicated variants, two exonic multiple
sclerosis SNPs in IFI30 (rs11554159) and TYK2
(rs34536443), respectively, are predicted as probably
damaging. For rs34536443 in TYK2, the protective allele
drives T lymphocyte differentiation towards a Th2 pheno-
type (Couturier et al., 2011). This variant was also found
to be associated with juvenile idiopathic arthritis, primary
biliary cirrhosis, psoriasis and rheumatoid arthritis (Eyre
et al., 2012; Liu et al., 2012; Tsoi et al., 2012; Hinks
et al., 2013). Other replicated SNPs included rs1800693
in TNFRSF1A, which functionality mimics the effect of
TNF blocking drugs (Gregory et al., 2012), and
rs2104286 in IL2RA, which seems to increase the ratio
of soluble/membrane IL2RA and inhibits IL2 signalling
(Maier et al., 2009). Both rs1800693 (TNFRSF1A) andrs2104286 (IL2RA) accounted for 450% of posteriorprobability of association in Europeans (IMSGC, 2013b).
In a previous study using an overlapping, albeit larger
sample set of African Americans, we reported signicant
associations for 8 of 74 tested non-MHC multiple sclerosis
risk SNPs with a two-tailed test P 5 0.01 threshold,whereas (coincidentally) 21 variants exceeded the one-
tailed test P5 0.05 threshold (Isobe et al., 2013). Whencompared to this study, all of these variants had the same
direction of association despite the limited statistical power
of both studies (Supplementary Table 2). However, associ-
ations in this study did not reach statistical signicance in
seven loci due most likely to the relatively low effect sizes
of these variants. Additionally, lower minor allele frequency
of the updated multiple sclerosis SNPs compared to the
previous SNPs prevented replication for two loci
(MMEL1 and IRF8). On the other hand, the TYK2 locus
was replicated, this time with a different risk-tagging SNP
from our previous study (rs8112449, not replicated; Isobe
et al., 2013).
Given the possibility of allelic heterogeneity across ances-
tral groups, we reasoned that SNPs lying close to the
European lead SNP have increased prior odds even if not
in linkage disequilibrium. To look for such effects we
searched in the African American data set for nominally
associated SNPs within the intervals anking each of the
110 European SNPs (with boundaries of the anking inter-
vals dened by the most distant SNP in linkage disequilib-
rium with the European lead SNP; r24 0.5 in the 1000Genome data set of Europeans). We considered rst the
21 intervals containing European lead SNPs that showed
nominal evidence of association, and found more signi-
cantly associated SNPs in 20 (data not shown). Among
them only eight were in linkage disequilibrium (r240.5)with the European lead SNP. In the remaining 89 regions
( = 110 21), after correction for independent testing ateach locus, and setting a FDR of 0.05, we found eight
regions that contained SNPs showing nominally signicant
evidence for association (Table 2, Figs 2 and 3, and
Supplementary Fig. 3). One of the variants (rs1861842)
in the PVT1/MIR1208 locus shows modest linkage disequi-librium (r2 = 0.409) with the corresponding lead European
SNP (rs759648) in the European population but rather
little linkage disequilibrium with that SNP in African
Americans (r2 = 0.142), suggesting that these two SNPs
(rs759648 and rs1861842) tag the same signal in
Europeans while only rs1861842 is correlated with the
signal in African Americans, consistent with this SNP
being a better tag for the functionally relevant variant
(Fig. 3A).
Taking advantage of the unique linkage disequilibrium
patterns in the African American genome enabled us to
possibly narrow two additional disease-association regions,
MMEL1 at 1p36 and ZFP36L1 at 14q22-q24. In the
MMEL1 locus, the linkage disequilibrium block in
African Americans (r24 0.5) anking rs111375644(lowest P-value in African Americans) is 2 494 8162 728 455bp and is 3.5 kb smaller than linkage disequilib-
rium block in Europeans anking rs3748817 (lowest
P-value in Europeans), excluding LOC115110 from the
candidate disease-associated genes (Fig. 3B). Furthermore,
the narrow linkage disequilibrium region (r24 0.8) aroundrs3748817 spreads across 237 kb in Europeans and in-
cludes ve genes, whereas the size of the high linkage dis-
equilibrium region in African Americans for rs111375644
was 16 kb and includes a single gene (TNFRSF14). In the
ZFP36L1 locus, the linkage disequilibrium region in
African Americans around the most signicantly associated
SNP rs8011424, was 25.6 kb smaller (69 265 911
69 310210bp) than that in Europeans anking the estab-
lished multiple sclerosis SNP (rs2236262), highlighting the
upstream region of ZFP36L1 (Supplementary Fig. 3D).
However, as these variants are monomorphic or show no
signicant linkage disequilibrium with their respective
European lead SNP even in the European population,
they may represent additional risk alleles rather than suc-
cessful ne mapping of European signals. Lastly, in the
IRF8 locus, the optimal SNP in African Americans after
imputation (rs13333054) coincides with the previously re-
ported SNP in the 2011 GWAS (IMSGC and WTCCC2,
2011) rather than the ImmunoChip (IMSGC, 2013b)(Supplementary Fig. 3E).
In this African American cohort 4 of 96 European lead
SNPs showed nominally signicant evidence of association
with the alternate allele to that seen in Europeans
(Supplementary Table 1), raising the possibility that these
variants might be exerting different, even opposite effects in
this population. However, this number of seemingly oppos-
ite effects is consistent with that expected to result from
random sampling variation overwhelming genuine but
modest signals. In a study of this size and considering 96
variants, we would anticipate seeing up to ve apparently
reversed effects by chance alone. A similar low frequency of
apparently reversed signals was seen in our previous
African American study (Isobe et al., 2013) and also in
1524 | BRAIN 2015: 138; 15181530 N. Isobe et al.
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Tab
le2
Alt
ern
ate
SN
Ps
inre
plicati
ng
kn
ow
nsu
scep
tib
ilit
yre
gio
ns
(A)
Eu
rop
ean
mu
ltip
lesc
lero
sis-
ass
ocia
ted
SN
Ps
(B)
To
pS
NP
inA
fric
an
Am
eri
can
sL
Din
fo(b
etw
een
Aan
dB
)e
rsID
(LD
regio
na)
Gen
eR
AA
fAm
rsID
cG
en
eR
AR
AF
OR
(95%
CI)
raw
pF
DRP
(No
.P
)dE
UR
AfA
m
OR
Pb
case
sco
nt.
R2
D
R2
D
rs3748817
(1:
24842721)
MMEL1
A1.0
52.4
10
01
rs111375644
TNFRSF14
(dis
t=
15959),
FAM213B
(dis
t=
6963)
G0.0
65
0.0
39
1.9
2(1
.432.5
8)
1.5
10
05
9.7
10
03
(664)
f
0.0
22
1.0
0
rs41286801
(1:
9268093373)
EVI5
A0.9
65.8
10
01
rs115126543
EVI5
(dis
t=
10883),
RPL5
(dis
t=
28750)
G0.0
22
0.0
08
3.0
6(1
.765.3
3)
7.9
10
05
2.4
10
02
(2697)
f
0.0
00
0.8
5
rs4679081
(3:
3297133014)
CCR4
(dis
t=
17080),
GLB1
(dis
t=
24617)
GN
Ars78553800
TRIM
71
(dis
t=
53040),
CCR4
(dis
t=
6255)
C0.9
56
0.9
26
1.5
8(1
.22-2
.06)
4.8
10
04
4.8
10
02
(268)
0.0
02
1.0
00.0
32
0.9
6
rs941816
(6:
36346-3
6384)
PXT1
G1.0
82.0
10
01
rs79281846
PXT1
A0.0
80
0.0
57
1.5
7(1
.222.0
3)
5.5
10
04
2.4
10
02
(98)
0.0
03
0.7
70.0
11
1.0
0
rs759648
(8:
129155129222)
PVT1
(dis
t=
45446),
MIR1208
(dis
t=
3417)
C0.9
67.3
10
01
rs1861842
MIR1208
(dis
t=
46226),
LINC00977
(dis
t=
1020053)
T0.3
92
0.3
28
1.3
0(1
.141.4
8)
8.5
10
05
4.3
10
03
(499)
0.4
09
0.9
90.1
42
0.6
3
rs2236262
(14:
6923369302)
ZFP36L1
A1.1
08.3
10
02
rs8011424
ZFP36L1
(dis
t=
9296),
ACTN1
(dis
t=
68584)
A0.2
53
0.2
14
1.3
5(1
.161.5
7)
8.4
10
05
1.7
10
02
(371)
0.0
19
1.0
00.1
24
1.0
0
rs35929052
(16:
8599486018)
IRF8
(dis
t=
38273),
LOC146513
(dis
t=
325553)
G1.0
63.7
10
01
rs13333054
IRF8
(dis
t=
54822),
LINC01082
(dis
t=
218754)
T0.2
55
0.2
04
1.3
6(1
.171.5
8)
6.0
10
05
8.7
10
03
(228)
0.0
36
1.0
00.0
08
1.0
0
rs1077667
(19:
66626676)
TNFSF14
G1.0
24.3
10
01
rs12150912
TNFSF14
(dis
t=
3775),
C3
(dis
t=
3472)
G0.6
51
0.6
29
1.2
4(1
.071.4
5)
5.2
10
03
2.5
10
03
(19)
0.3
44
0.9
90.0
71
1.0
0
aR
egi
ons
are
defined
asra
nge
ofposi
tions
where
SNPs
inlin
kag
edis
equili
bri
um
(r24
0.5
)w
ith
the
multip
lesc
lero
sis-
asso
ciat
ed
SNPs
inEuro
pean
softh
e1000
Genom
ePro
ject
loca
te.C
hro
moso
me
num
ber
and
genom
icposi
tions
(hum
ange
nom
e19,
kb)
are
show
n.
bO
ne-t
aile
dte
st.
cIm
pute
dSN
Ps
are
show
nin
ital
ics.
dFa
lse
dis
cove
ryra
teP-
valu
es
are
show
nw
ith
the
num
ber
of
SNPP-
valu
es
inlin
kag
edis
equili
bri
um
regi
ons
inbra
ckets
.eLin
kag
edis
equili
bri
um
info
rmat
ion
inEuro
pean
sori
ginat
ed
from
Euro
pean
dat
ase
tof
the
1000
Genom
ePro
ject
and
that
inA
fric
anA
meri
cans
are
from
our
Afr
ican
Am
eri
can
dat
ase
t.f T
op
SNP
inlin
kag
edis
equili
bri
um
regi
on
(B)
ism
onom
orp
hic
inEuro
pean
s.
AfA
m=
Afr
ican
Am
eri
cans;
Chr
=ch
rom
oso
me;C
I=
confidence
inte
rval
;dis
t=
dis
tance
;EU
R=
Euro
pean
s;LD
=lin
kag
edis
equili
bri
um
;M
AF
=m
inor
alle
lefr
equency
;N
A=
not
avai
lable
;O
R=
odds
ratio;R
A=
risk
alle
lein
Euro
pean
s;
SE=
stan
dar
derr
or.
ImmunoChip in African Americans with MS BRAIN 2015: 138; 15181530 | 1525
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Figure 3 Narrowing in the causative region using African American data set. Comparative association plots for the loci of (A) PVT1/
MIR1208 and (B) MMEL1 of (i) African Americans after fine mapping with imputation; and (ii) the discovery data set of European ImmunoChip.
SNPs with the top association P-values are shown in purple with SNP IDs. For the plots of African Americans, genotyped SNPs are shown in
closed circles and imputed ones in closed triangles. Colours of the marks represent linkage disequilibrium (r2) with the top SNP in each
population. Chromosomal positions are based on human genome 19. Note differences in the scales of y-axis.
1526 | BRAIN 2015: 138; 15181530 N. Isobe et al.
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our study of European multiple sclerosis variants in an
Indian data set (Pandit et al., 2011). Although such allele
ipping could theoretically have resulted from unusual
population-based differences in allele frequencies (Lin
et al., 2007; Zaykin and Shibata, 2008; Clarke and
Cardon, 2010), no such differences are apparent in the
1000 Genomes data set (The 1000 Genomes Project
Consortium, 2010), where the minor allele for these four
SNPs is the same in both populations.
Exploring potential associationoutside the established multiplesclerosis-associated loci
Recognizing the limited power of the data set, we never-
theless explored the evidence for association seen at SNPs
mapping outside the designated 110 multiple sclerosis loci
and outside the MHC region. In this analysis we identied
seven regions containing at least one SNP with P5 104
(Supplementary Table 3). Only one of these (rs11123495)
showed nominally signicant association in the European
ImmunoChip data set (P = 1.98 102) but the directionof the association was opposite from that in African
Americans (IMSGC, 2013b). When analysing these seven
regions in an independent replication cohort (620 African
American cases with multiple sclerosis and 1565 control
subjects), we found evidence of association for only one
variant (rs2702180 in SMG7) (one-tailed test P = 0.034,
Table 3). However, in a combined analysis across both
African American data sets, this SNP failed to reach
genome-wide signicance (P = 6.3 105).
DiscussionThe recent completion of the ImmunoChip project raised to
110 the number of non-MHC multiple sclerosis risk DNA
variants in Europeans (IMSGC, 2013b). In aggregate, the
proportion of the genetic variance accounting for disease
risk explained by these polymorphisms, including the
MHC, is roughly 27% (IMSGC, 2013b). Our main goal
was to assess the transferability of this updated multiple
sclerosis genetic map to African Americans. The number
of replicated variants (21 of 96) was within the range of
expectation given the power of our study, suggesting that
most, if not all of the multiple sclerosis risk SNPs dis-
covered in Europeans are also relevant in African
Americans and possibly in other non-white populations as
well. An excess of concordant direction for allelic effects of
the European multiple sclerosis SNPs in African Americans
is consistent with this generalization.
For several of the established loci even though we failed
to see evidence for signicant association with the
European lead SNP, we did nd evidence of association
with independent anking variants. Most of these new vari-
ants were uncorrelated with the European lead SNP in both Tab
le3
Rep
licati
on
of
can
did
ate
no
vel
mu
ltip
lesc
lero
sis-
ass
ocia
ted
loci
inA
fric
an
Am
eri
can
s
To
pS
NP
saft
er
imp
uta
tio
nR
ep
licati
on
stu
dy
Meta
-an
laysi
saR
egio
nal
top
SN
Pin
Eu
rop
ean
ICb
Ch
rrs
IDc
Po
siti
on
Gen
ed
RA
RA
FO
R(9
5%
CI)
Pe
RA
Ff
OR
Pg
OR
(95%
CI)
Prs
IDP
osi
tio
nR
AO
R(9
5%
CI)
Ph
case
sco
nt.
case
sco
nt.
1rs
2702180
183517971
SMG7
T0.7
40.7
01.3
1(1
.141.5
0)
1.3
10
04
0.7
40.7
11.1
53.4
10
02
1.2
3(1
.111.3
6)
5.3
10
05
rs789176
183512840
A1.0
5(1
.001.1
0)
5.6
10
02
2rs1438856
119570839
(EN1)
A0.3
20.2
61.4
0(1
.211.6
2)
6.2
10
06
0.2
50.2
80.8
39.9
10
01
1.0
9(0
.981.2
1)
1.1
10
01
rs11123495
119577577
A1.0
5(1
.011.0
9)
2.0
10
02
8rs
6986146
i6197182
(LOC100287015)
T0.2
60.2
01.3
5(1
.161.5
6)
6.3
10
05
0.2
10.2
20.9
08.9
10
01
1.1
2(1
.011.2
5)
3.6
10
02
rs6986146
6197182
G1.0
1(0
.981.0
4)
6.1
10
01
12
rs10848633
2316019
CACNA1C
G0.2
80.2
11.4
2(1
.231.6
4)
6.9
10
06
0.2
20.2
11.0
52.7
10
01
1.2
3(1
.11.3
7)
2.0
10
04
rs11062158
2325978
G1.1
0(1
.001.2
1)
4.1
10
02
12
rs10860696
101559080
SLC5A8
T0.2
90.2
41.4
0(1
.211.6
2)
7.2
10
06
0.2
80.2
80.9
85.9
10
01
1.1
7(1
.061.3
0)
2.7
10
03
rs12313149
101584223
C1.0
1(0
.971.0
6)
6.8
10
01
20
rs6047667
21827351
(PAX1)
G0.3
60.2
91.4
3(1
.231.6
6)
2.6
10
06
0.3
00.3
10.9
57.8
10
01
1.1
5(1
.041.2
7)
8.0
10
03
rs2180439
21853100
G1.0
1(0
.981.0
5)
5.0
10
01
Posi
tion
isbas
ed
on
hum
ange
nom
e19
and
dbSN
P137.Lis
tof
genoty
ped
top
SNPs
with
asso
ciat
ionP5
10
4ar
esh
ow
nin
Supple
menta
ryTab
le3.A
ssay
faile
din
one
of
the
seve
nca
ndid
ate
loci
.aFi
xed
modelis
applie
d.
bR
egi
ons
are
defined
asra
nge
of
posi
tions
where
SNPs
inlin
kag
edis
equili
bri
um
(r24
0.5
)w
ith
the
top
SNPs
afte
rim
puta
tion
inA
fric
anA
meri
cans
of
the
1000
Genom
ePro
ject
loca
te.
cIm
pute
dSN
Ps
are
show
nin
ital
ics.
dW
hen
SNPs
loca
tein
terg
enic
,th
ecl
ose
stge
nes
are
show
nin
bra
ckets
.eSN
PT
EST
was
use
dfo
rth
eas
soci
atio
nte
stin
the
impute
ddat
ase
tw
hile
PLIN
Kw
asuse
dfo
rth
ete
stin
the
genoty
ped
dat
ase
tbefo
reim
puta
tion.H
ere
,P-
valu
es
from
SNPT
EST
were
show
n.
f Ris
kal
lele
sar
eth
ose
inth
edis
cove
rydat
ase
t.gO
ne-t
aile
dte
st.
hW
hen
multip
leco
rrect
ion
was
conduct
ed
for
the
SNPs
avai
lable
ineac
hlin
kag
edis
equili
bri
um
regi
on
with
FDR
meth
ods,
the
FDRP-
valu
es
(no.SN
Ps
ineac
hlo
cus)
were
P=
7.7
10
01
(n=
133)
for
rs789176,P
=2.1
10
02
(n=
2)
for
rs11123495,P
=6.1
10
01
(n=
1)
for
rs6986146,P
=8.3
10
01
(n=
78)
for
rs11062158,P
=7.3
10
01
(n=
3)
for
rs12313149,an
dP
=5.0
10
01
(n=
1)
for
rs2180439.
i As
replic
atio
nof
the
top
SNP
afte
rim
puta
tion,rs
6986480
faile
d,th
eto
pge
noty
ped
SNP
was
use
dfo
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the African American and European populations, suggest-
ing that these must be different effects although the possi-
bility of artefacts cannot be excluded. However, for one
variant (rs1861842 adjacent to MIR1208) we did see link-
age disequilibrium in the European population but not in
the African American population, indicating that the ori-
ginal disease risk signal has been successfully ne mapped
beyond what was possible within the European population.
Altogether, our data conrm that the potential of less ex-
tensive linkage disequilibrium structure present in African
Americans to aid in ne mapping is only likely to be ad-
vantageous if the study has adequate power to demonstrate
signicant genome-wide association.
The signal we identied in the region of MMEL1, locates
telomeric to MMEL1, between FAM213B and TNFRSF14,
whereas the European signal locates to the 18th intron of
MMEL1 itself. This increases the evidence supporting a
role for these other genes. FAM213B is associated with
biosynthesis of prostaglandin F2 and cyclooxygenase path-
way whereas TNFRSF14, a member of the TNF receptor
superfamily ts well within the activatory/inhibitory inam-
mation pathways mechanistically associated with multiple
sclerosis (IMSGC and WTCCC2, 2011). Mutations in
TNFRSF14 have also been associated with B cell lymph-
oma (Morin et al., 2011; Lohr et al., 2012), consistent with
an increasing appreciation that disordered B cell function is
intimately associated with multiple sclerosis pathogenesis
(Hauser and Goodin, 2012). Interestingly, a recent net-
work-based pathway analysis also ranked TNFRSF14
higher compared to MMEL1 as a multiple sclerosis suscep-
tibility locus (IMSGC, 2013a). Similarly, for EVI5 on
chromosome 1, which is a well-established risk locus with
relatively large effect size (odds ratio = 1.20) (IMSGC,
2013b), the reported top risk-tagging SNP in Europeans
locates at the 3 untranslated region (UTR) of EVI5,while in African Americans, the associated SNP
(rs115126543) identied in this study locates 11 kb up-
stream of the gene itself within transcription factor binding
sites and a DNase I hypersensitive site (Bernstein et al.,
2012), suggesting a role for transcriptional regulatory
mechanisms mediating risk. However, it is notable that
risk allele frequencies for both these variants are low and
therefore so is power. As neither is identied with clear
signicance additional studies will be required to conrm
the relevance of these observations.
The screen identied seven novel regions containing at
least one SNP with suggestive evidence of association, of
which only one (rs2702180 in SMG7 on chromosome 1)
replicated in an independent data set using relatively lenient
but predetermined replication criteria. SMG7 encodes a
protein that is essential for nonsense-mediated mRNA
decay, a process linked to autoimmunity (Bachmann
et al., 2006). Interestingly, the risk-tagging SNP was re-
ported to be associated with the expression level of
SMG7 in brain tissues (Gibbs et al., 2010) and in lympho-
blastoid cells (Stranger et al., 2007). In SLE, NCF2 adjacent
to SMG7 is reported to be associated with the disease
(Gateva et al., 2009; Cunninghame Graham et al., 2011;
Jacob et al., 2012) but a multi-ethnic study pointed out that
SLE-associated variants located in NCF2 were signicantly
associated with the expression of SMG7 (Kim-Howard
et al., 2014). Additional studies will be required to validate
the association in an independent African American data
set with larger sample size and to determine if the associ-
ation with this locus can also be observed in European
populations. The SMG7 region locates outside the highest
peak in a genome-wide admixture scan, which may par-
tially explain why the multiple sclerosis association with
SMG7/NCF2 was found in African Americans but not in
Europeans (Reich et al., 2005).
In conclusion, we show the extensive replication of
European multiple sclerosis variants in African Americans,
consistent with a shared genetic architecture for multiple
sclerosis susceptibility across these different populations.
However, as the ImmunoChip design was mainly based
on reference European populations (Cortes and Brown,
2011), the utility of the array to genotype non-European
populations, potentially lacking tag SNPs for some haplo-
types and the full range of cross-ancestral genetic plei-
otropy, remains unknown. Our results suggest that
ImmunoChip-like platforms have substantial potential to
ne-map regions of interest by taking advantage of differ-
ent haplotypic structures, but the need for very large
sample sizes and functional studies is still evident. Even
with arrays capable of tagging variation in both popula-
tions, very large sample sizes would be necessary to exclude
any modest effect of a European variant in an African
American population and vice versa. Trans-ancestral stu-
dies are also likely to help in the discovery of new genes
and pathways vital to disease susceptibility (Diabetes
Genetics Replication and Meta-analysis Consortium et al.,
2014). In addition, the clinical expression of multiple scler-
osis, including its severity, is known to have a genetic basis,
but to date no disease modiers have been convincingly
identied. The severe clinical course and treatment-resist-
ance typical of multiple sclerosis in African Americans
highlights an additional opportunity, i.e. to identify modi-
ers of disease severity and progression that could lead to
much-needed therapeutic opportunities.
Supplementary materialSupplementary material is available at Brain online.
AcknowledgementsThe authors thank the multiple sclerosis patients and
healthy controls who participated in this study. The au-
thors acknowledge the contributions of H. Mousavi and
R. Guerrero (UCSF) for sample processing and manage-
ment, and the genotyping teams at the Wellcome Trust
Sanger Institute, UK, the Cambridge NIHR Biomedical
1528 | BRAIN 2015: 138; 15181530 N. Isobe et al.
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Research Centre, UK and the Centre for Public Health
Genomics, University of Virginia, Charlottesville, VA,
USA. This manuscript is dedicated to the memory of
Joseph Herbert, in recognition of his contributions and
leadership in multiple sclerosis research, and committed
dedication to people aficted with the disease.
FundingThis study is supported by grants from the National
Institute of Health (R01NS076492, R01NS046297 and
R01NS049477) and the UK Multiple Sclerosis Society
(898/08). Recruitment of study participants and sample ac-
quisition was supported by National Multiple Sclerosis
Society (RG2899-D11 and RC2 GM093080). N.I. was sup-
ported by Postdoctoral Fellowship for Research Abroad
from Japan Society for the Promotion of Science (JSPS)
and is currently a JSPS Research Fellow. L.P. is a Harry
Weaver Neuroscience Scholar of the National Multiple
Sclerosis Society (JF2144A2/1).
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