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Latitude and HLA-DRB1*04:05 independently influence disease severity in Japanese multiple sclerosis: a cross-sectional study

  • 1,
  • 1,
  • 1,
  • 2,
  • 3,
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  • 4,
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  • 4,
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  • 1Email author and
Journal of Neuroinflammation201613:239

https://doi.org/10.1186/s12974-016-0695-3

  • Received: 13 January 2016
  • Accepted: 20 August 2016
  • Published:

Abstract

Background

Higher latitude and human leukocyte antigen (HLA)-DRB1*04:05 increase susceptibility to multiple sclerosis (MS) in the Japanese population, but their effects on disease severity are unknown. We aimed to clarify the effects of latitude and the HLA-DRB1 and HLA-DPB1 genes on disease severity in Japanese patients with MS.

Methods

We enrolled 247 MS patients and 159 healthy controls (HCs) from the northernmost main island of Japan, Hokkaido Island (42–45° north), and 187 MS patients and 235 HCs from the southern half (33–35° north) of the Japanese archipelago (33–45° north). We genotyped HLA-DRB1 and HLA-DPB1 alleles, compared demographic features, and analyzed factors contributing to differences in clinical and laboratory findings between MS patients from southern and northern Japan. The Multiple Sclerosis Severity Score (MSSS), which adjusts the Kurtzke’s Expanded Disability Status Scale score according to disease duration, was used to estimate disease severity.

Results

The HLA-DRB1*04:05 and DRB1*15:01 alleles conferred susceptibility to MS in our Japanese population (p corr = 0.0004 and p corr = 0.0019, respectively). Southern patients had higher MSSS scores than northern patients (p = 0.003). Northern patients had higher frequencies of brain lesions meeting the Barkhof criteria (Barkhof brain lesions) and cerebrospinal fluid (CSF) IgG abnormalities than southern patients (p = 0.0012 and p < 0.0001, respectively). DRB1*04:05-positive MS patients had lower MSSS scores and lower frequencies of Barkhof brain lesions and CSF IgG abnormalities than DRB1*04:05-negative MS patients (p = 0.0415, p = 0.0026, and p < 0.0001, respectively). Multivariate analyses revealed that latitude and DRB1*04:05 were independently associated with the lowest quartile of MSSS and that latitude was positively associated with Barkhof brain lesions and CSF IgG abnormalities. DRB1*04:05 was negatively associated with these parameters. MSSS was decreased by 0.57 per DRB1*04:05 allele (p = 0.0198).

Conclusions

Living at a higher latitude and carrying the DRB1*04:05 allele independently lessens MS symptom severity as defined by MSSS. However, these factors influence the frequency of Barkhof brain lesions and CSF IgG abnormalities in opposite ways; higher latitude increases the frequency of Barkhof brain lesions and CSF IgG abnormalities, whereas DRB1*04:05 decreases them.

Keywords

  • Multiple sclerosis
  • HLA
  • Latitude
  • Magnetic resonance imaging
  • Oligoclonal IgG bands

Background

Multiple sclerosis (MS) is a chronic disease of the central nervous system characterized by inflammation, demyelination, and axonal injury [1]. MS susceptibility and phenotypes result from complex interactions between multiple genetic and environmental factors [2]. It is well established that the class II subregion of the human leukocyte antigen (HLA) gene on chromosome 6p21 plays the most important role in determining MS susceptibility [3]. The DR15 haplotype (DRB1*15:01-DQA1*01:02-DQB1*06:02) is strongly associated with MS, and the effect is mainly driven by HLA-DRB1*15:01 in people of northern European descent [4, 5]. Although DRB1 alleles clearly influence MS susceptibility, it is not known how HLA variation influences the clinical features of MS, especially in Asian populations.

We previously reported that the HLA-DRB1*04:05 allele is the strongest genetic risk factor for MS in the southern Japanese population. The clinical phenotypes of patients with the HLA-DRB1*04:05 allele include a milder clinical course, younger age at disease onset, slower disease progression, fewer brain lesions, and rare cerebrospinal fluid (CSF) IgG abnormalities compared with patients lacking the HLA-DRB1*04:05 allele [6]. It is widely known that the risk for MS increases with distance from the equator [7], suggesting that environmental risk factors related to latitude, such as decreased sunlight exposure and vitamin D levels, are involved [8]. Additionally, despite genetic homogeneity, there are phenotypic differences between northern and southern Japanese patients with MS. In the fourth nationwide survey in Japan, brain magnetic resonance imaging (MRI) findings fulfilling the Barkhof criteria [9] were significantly more common in northern patients than in southern patients and more frequent in northern-born northern residents than northern-born southern residents [10]. Recent studies in Western countries have revealed an association between latitude and the presence of oligoclonal IgG bands (OB) or increased intrathecal production of IgG [11, 12]. We have also reported that latitude independently affects the emergence of CSF IgG abnormalities in Japanese patients with MS [13].

These observations suggest that latitude may influence the clinical phenotype of MS. However, the relationship between latitude and disease severity still remains unclear. Thus, the aim of this study was to clarify the influence of latitude and HLA-DRB1 on disease severity in Japanese patients with MS.

Methods

Participants

Patients with MS, agreeing to participate in this study, were recruited from nine institutes in Japan. MS was diagnosed using the 2010 revised McDonald criteria [14]. Patients with neuromyelitis optica [15], neuromyelitis optica spectrum disorders [16], or longitudinally extensive spinal cord lesions extending over three or more vertebral segments were excluded. Patients with primary progressive MS (PPMS) were also excluded because of the low prevalence of PPMS in the Japanese population [10], as well as the association between PPMS and distinct HLA class II alleles from relapse-onset MS [17, 18]. Participants were recruited from the northern and southern parts of the Japanese archipelago, which spans 33–45° north (Additional file 1: Figure S1). Patients recruited from Hokkaido Island, the northernmost main island of Japan (42–45° north), were classified as the northern group, and those recruited from the southern half of the Japanese archipelago (33–35° north) were classed as the southern group. Patients residing on Hokkaido were chosen for the northern group because most people living on Hokkaido are descendants of immigrants who came from the other main islands 100–150 years ago, during the Meiji era, and thus share similar genetic makeup with modern inhabitants of the other main islands [10]. These populations were considered suitable for studying the effects of latitude, because of the latitude difference of at least 7° between Hokkaido Island and southern Japan. In total, 247 patients with MS and 159 healthy controls (HCs) in the northern group, and 187 patients with MS and 235 HCs in the southern group, participated in this study. Although sex and age were not matched between MS patients and HCs, HCs were used only for comparing HLA phenotypic frequency. Therefore, we believe that the use of unmatched HCs would not distort our results. We collected the demographic and clinical data of the participants including sex, age, age at disease onset, disease duration, MS subtype, annualized relapse rate (ARR), Kurtzke’s Expanded Disability Status Scale (EDSS) [19] score, and Multiple Sclerosis Severity Score (MSSS) [20] at the time of DNA blood sampling. Fulfillment of the Barkhof criteria for MS [9], positivity of CSF OB (determined by isoelectric focusing) [21], and abnormality of IgG index as calculated by (CSF IgG/serum IgG)/(CSF albumin/serum albumin) were determined by retrospective review of each participant’s medical records. In all patients, the presence of OB in CSF was assessed in a single laboratory (LSI Medience Corporation, Tokyo, Japan) and EDSS scores measured during remission were used. MSSS, which adjusts the EDSS score according to disease duration, was used to estimate the disease severity for each individual patient on a cross-sectional basis [20]. We defined the presence of Barkhof brain lesions by fulfillment of the four dichotomized MRI parameters proposed by Barkhof et al.: (1) the presence of at least one gadolinium-enhancing lesion or nine T2 hyperintense lesions, (2) the presence of at least one infratentorial lesion, (3) the presence of at least one juxtacortical lesion, and (4) the presence of at least three periventricular lesions [9]. We included cerebellar lesions as infratentorial lesions in the criteria. The IgG index was considered to be elevated if it was >0.658 [22]. We defined secondary progressive MS (SPMS) as a sustained increase in ≥1 point when EDSS was ≤5.5 and as a sustained increase in EDSS of ≥0.5 point when EDSS was ≥6.0 [23]. Benign MS was defined by an EDSS score of ≤2.0 at least 10 years after disease onset [24]. Patients and HCs were recruited from June 2012 to January 2013 in the northern group and from April 2006 to January 2013 in the southern group [6]. As the prevalence of MS is lower in southern Japan than in northern Japan [25], a longer recruitment period was allowed in the southern group. The sample sizes required to reveal an association of the HLA-DRB1*04:05 allele with MS were calculated to be 122 cases and 122 controls, based on our previous report [6]. We also collected clinical data from 109 of the 187 southern patients up to January 2013 to adjust for the different recruitment periods between the groups. The ethics committees of each institution approved this study, and written informed consent was obtained from all participants.

HLA-DRB1 and HLA-DPB1 genotyping

The genotypes of the participants HLA-DRB1 and HLA-DPB1 alleles were determined by hybridization between polymerase chain reaction amplification products of the HLA-DRB1 and HLA-DPB1 genes and sequence-specific oligonucleotide probes, as previously described [26].

Statistical analysis

The phenotypic frequencies of the HLA-DRB1 and HLA-DPB1 alleles were compared using either the chi-square test or Fisher’s exact probability test (when criteria for the chi-square test were not fulfilled). The chi-square test was used to compare sex, SPMS, brain MRI lesions meeting the Barkhof criteria, and CSF IgG abnormalities between subgroups. We performed the Shapiro–Wilk test for normality for continuous variables, such as age, age at onset, disease duration, ARR, EDSS, and MSSS. As these continuous variables were not normally distributed, we used the Mann–Whitney U test for comparisons between subgroups. The Mann–Whitney U test was also used to compare MSSS between patients with and without Barkhof brain lesions and between patients with and without CSF IgG abnormalities.

A multivariate linear regression model was used for continuous dependent variables (log-transformed age at onset), while a logistic regression model was used for binary dependent variables (benign MS, fulfillment of Barkhof criteria for MS, and CSF IgG abnormalities), adjusting for other factors associated with dependent variables. We divided MSSS into quartiles defined by MSSS values of 0.94, 2.60, and 5.50, and a logistic regression model was used. All analyses were performed using JMP 11.0.0 (SAS Institute Inc., Cary, NC, USA). Statistical significance was set at p < 0.05. Uncorrected p values (p uncorr) were corrected by multiplying them by the number of comparisons (Bonferroni–Dunn’s correction) to calculate corrected p values (p corr).

Results

Demographic features

The clinical features of the 434 patients with MS (314 females, 120 males) are summarized in Table 1. The median age at disease onset was 29 years (interquartile range 22–38 years). The frequency of SPMS was 17.1 %. The median EDSS score was 2.0 (interquartile range 1.0–3.5), and the median MSSS was 2.60 (interquartile range 0.94–5.50). A total of 318 patients (74.3 %) had Barkhof brain lesions, and 193 patients (58.7 %) had CSF IgG abnormalities.
Table 1

Demographic features of patients with MS according to region

 

Total patients (n = 434)

Northern patients (n = 247)

Southern patients (n = 187)

p value

Number of males/females (ratio)

120/314 (1:2.6)

62/185 (1:3.0)

58/129 (1:2.2)

NS

Age (years)a

41 (33–50)

41 (34–50)

40 (32–50)

NS

Age at onset (years)a

29 (22–38)

29 (22–36)

30 (23–40)

NS

SPMS (%)

73/427 (17.1)

53/245 (21.6)

20/182 (11.0)

0.0039

Disease duration (years)a

9 (4–15)

10 (6–17)

6.5 (3–13)

<0.0001

EDSSa

2.0 (1.0–3.5)

2.0 (1.0–3.5)

2.0 (1.0–3.5)

NS

MSSSa

2.60 (0.94–5.50)

2.13 (0.69–5.24)

3.54 (1.45–5.90)

0.003

ARRa

0.41 (0.22–0.75)

0.41 (0.24–0.73)

0.40 (0.20–0.89)

NS

Barkhof criteria (%)

318/428 (74.3)

198/247 (80.2)

120/181 (66.3)

0.0012

Positive OB and/or increased IgG index (%)

193/329 (58.7)

130/177 (73.5)

63/152 (41.5)

<0.0001

Phenotypic frequency of HLA-DRB1*04:05 (%)

172 (39.6)

92 (37.3)

80 (42.8)

NS

Phenotypic frequency of HLA-DRB1*15:01 (%)

125 (28.8)

75 (30.4)

50 (26.7)

NS

The Mann–Whitney U test was used to compare continuous variables, and the chi-square test was used to compare categorical variables

ARR annualized relapse rate, EDSS Kurtzke’s Expanded Disability Status Scale, MSSS Multiple Sclerosis Severity Score, NS not significant, OB oligoclonal IgG bands, SPMS secondary progressive multiple sclerosis

aMedian (interquartile range)

Frequencies of the HLA-DRB1 and HLA-DPB1 alleles

As shown in Table 2, the phenotypic frequencies of the DRB1*04:05 and DRB1*15:01 alleles were significantly higher in MS patients than HCs (p corr = 0.0004 and p corr = 0.0019, respectively). The phenotypic frequencies of DRB1*01:01, DRB1*09:01, DRB1*13:02, and DRB1*15:02 were significantly lower in MS patients than HCs (p corr = 0.003, p corr = 0.0198, p corr = 0.0066, and p corr = 0.0396, respectively). No DPB1 alleles were associated with MS in Japan (Additional file 2: Table S1). Compared with HCs, the phenotype frequency of DRB1 * 04:05 was significantly higher in patients with MS in both northern and southern regions (p corr = 0.0224 and p corr = 0.0384, respectively) (Additional file 2: Tables S2 and S3). There was no significant difference in the distribution of DRB1 alleles between northern and southern HCs (Additional file 2: Table S4).
Table 2

Phenotypic frequencies of HLA-DRB1 alleles in patients with MS

DRB1

Phenotype frequency, n (%)

OR

95 % CI

p uncorr

p corr

MS (n = 434)

HCs (n = 394)

01:01

24 (5.5)

53 (13.5)

0.38

0.23–0.62

<0.0001

0.003

03:03

1 (0.2)

0

NA

NA

1.0000

NS

04:01

7 (1.6)

9 (2.3)

0.70

0.26–1.90

0.6151

NS

04:03

42 (9.7)

22 (5.6)

1.81

1.06–3.09

0.0276

NS

04:04

2 (0.5)

2 (0.5)

0.91

0.13–6.47

1.0000

NS

04:05

172 (39.6)

100 (25.4)

1.93

1.43–2.60

<0.0001

0.0004

04:06

42 (9.7)

26 (6.6)

1.52

0.91–2.52

0.1071

NS

04:07

2 (0.5)

4 (1.0)

0.45

0.08–2.48

0.4317

NS

04:10

24 (5.5)

8 (2.0)

2.82

1.25–6.36

0.0091

NS

07:01

1 (0.2)

2 (0.5)

0.45

0.04–5.01

0.6073

NS

07:10

1 (0.2)

0

NA

NA

1.0000

NS

08:01

1 (0.2)

1 (0.3)

0.91

0.06–14.56

1.0000

NS

08:02

38 (8.8)

29 (7.4)

1.21

0.73–2.00

0.4622

NS

08:03

63 (14.5)

56 (14.2)

1.02

0.69–1.51

0.9012

NS

09:01

72 (16.6)

104 (26.4)

0.55

0.40–0.78

0.0006

0.0198

10:01

2 (0.5)

2 (0.5)

0.91

0.13–6.47

1.0000

NS

11:01

18 (4.2)

19 (4.8)

0.85

0.44–1.65

0.6388

NS

12:01

26 (6.0)

38 (9.6)

0.60

0.36–1.00

0.0493

NS

12:02

5 (1.2)

15 (3.8)

0.29

0.11–0.82

0.0211

NS

13:01

3 (0.7)

2 (0.5)

1.36

0.23–8.21

1.0000

NS

13:02

20 (4.6)

46 (11.7)

0.37

0.21–0.63

0.0002

0.0066

13:07

0

1 (0.3)

0

NA

0.4758

NS

14:01

3 (0.7)

0

NA

NA

0.2508

NS

14:02

1 (0.2)

1 (0.3)

0.91

0.06–14.56

1.0000

NS

14:03

20 (4.6)

14 (3.6)

1.31

0.65–2.63

0.4449

NS

14:05

17 (3.9)

15 (3.8)

1.03

0.51–2.09

0.9347

NS

14:06

11 (2.5)

6 (1.5)

1.68

1.62–4.59

0.3371

NS

14:07

0

2 (0.5)

0

NA

0.2261

NS

14:54

20 (4.6)

28 (7.1)

0.63

0.35–1.14

0.1245

NS

15:01

125 (28.8)

67 (17.0)

1.97

1.41–2.76

<0.0001

0.0019

15:02

55 (12.7)

83 (21.1)

0.54

0.37–0.79

0.0012

0.0396

15:10

1 (0.2)

0

NA

NA

1.0000

NS

16:02

4 (0.9)

4 (1.0)

0.91

0.23–3.65

1.0000

NS

p uncorr was corrected by multiplying the value by 33 to calculate p corr

CI confidence interval, HCs healthy controls, MS multiple sclerosis, NA not applicable, NS not significant, OR odds ratio, p corr corrected p value

Comparison of clinical characteristics between northern and southern patients

Northern MS patients had significantly lower MSSS scores compared with southern patients (p = 0.003) (Table 1), although the frequency of SPMS was higher in the north than in the south (p = 0.0039). Northern patients had a significantly longer disease duration, a higher frequency of Barkhof brain lesions, and a higher frequency of CSF IgG abnormalities compared with southern patients (p < 0.0001, p = 0.0012, and p < 0.0001, respectively). Even after excluding all SPMS patients, northern patients had a significantly longer disease duration, lower EDSS and MSSS, and higher frequencies of Barkhof brain lesions and CSF IgG abnormalities compared with southern patients (p = 0.0004, p = 0.0008, p < 0.0001, p = 0.0217, and p < 0.0001, respectively) (Additional file 2: Table S5). Similar results were seen when comparing MS patients between northern and southern Japan. There were no significant differences in the phenotypic frequencies of HLA-DRB1 04:05 and HLA-DRB1 15:01 between northern and southern patients (37.3 vs. 42.8 %, p = 0.2432; 30.4 vs. 26.7 %, p = 0.4087, respectively) (Table 1). After excluding all SPMS patients, there were still no differences in the frequencies of either allele between northern and southern patients (HLA-DRB1 04:05, 37.6 vs. 43.7 %, p = 0.2403; HLA-DRB1 15:01, 30.9 vs. 27.5 %, p = 0.4816) (Additional file 2: Table S5).

When we compared the demographic features of northern and southern patients with using clinical data from southern patients that were followed up until January 2013, there were no significant differences in disease duration, EDSS, or MSSS, although SPMS frequency was significantly higher in northern Japan (p = 0.0256) (Additional file 2: Table S6). When we excluded SPMS patients from the MS patient group, to adjust for the different recruitment periods, the northern patients had significantly lower MSSS (median 1.45 vs. 2.23, p = 0.0411) (Additional file 2: Table S7).

We examined the association of MSSS with Barkhof brain lesions and CSF IgG abnormalities and found that neither was associated with MSSS in the total population nor in the northern or southern MS patient populations (Additional file 2: Table S8).

Comparison of clinical characteristics between HLA-DRB1*04:05-positive and HLA-DRB1*04:05-negative patients

MS patients with DRB1*04:05 were younger at disease onset, had a lower MSSS score, and had lower frequencies of Barkhof brain lesions and CSF IgG abnormalities than those without DRB1*04:05 (p = 0.0003, p = 0.0415, p = 0.0026, and p < 0.0001, respectively) (Table 3). In southern MS patients, DRB1*04:05 carriers were younger and had an earlier onset, longer disease duration, lower EDSS and MSSS scores, and lower frequencies of Barkhof brain lesions and CSF IgG abnormalities than non-DRB1*04:05 carriers (p = 0.0334, p = 0.0001, p = 0.0133, p = 0.0263, p = 0.0021, p = 0.0143, and p = 0.008, respectively). In northern patients, DRB1*04:05 carriers also had a lower frequency of CSF IgG abnormalities than non-DRB1*04:05 carriers (p = 0.0007), while age at onset, MSSS, and Barkhof brain lesion frequency in northern patients showed similar trends to the southern patients, but were not significantly different between DRB1*04:05 carriers and non-DRB1*04:05 carriers.
Table 3

Comparison of the clinical features of patients with MS according to the presence or absence of HLA-DRB1*04:05

DRB1

Total patients

Northern patients

Southern patients

04:05 (+) (n = 172)

04:05 (−) (n = 262)

p value

04:05 (+) (n = 92)

04:05 (−) (n = 155)

p value

04:05 (+) (n = 80)

04:05 (−) (n = 107)

p value

Number of males/females (ratio)

52/120 (1:2.3)

68/194 (1:2.9)

NS

27/65 (1:2.4)

35/120 (1:3.4)

NS

25/55 (1:2.2)

33/74 (1:2.2)

NS

Age (years)a

39 (31–49)

42 (34.2–51.5)

0.0259

41 (34–49.5)

42 (35–51)

NS

36 (28–49)

42 (34–52)

0.0334

Age at onset (years)a

26 (21–34.8)

30.2 (24–40)

0.0003

27 (21–34)

29 (24–37)

NS

25 (20–36.8)

33 (26–43)

0.0001

SPMS (%)

26/170 (15.3)

47/257 (18.3)

NS

19/92 (20.7)

34/153 (22.2)

NS

7/78 (9.0)

13/104 (12.5)

NS

Disease duration (years)a

9 (5.3–16)

9 (4–14)

NS

10 (6–17)

11 (5–17)

NS

7.5 (4–14.8)

5.5 (3–10.3)

0.0133

EDSSa

2.0 (1.0–3.5)

2.0 (1.0–3.5)

NS

2.0 (1.0–3.5)

2.0 (1.0–3.5)

NS

2.0 (1.0–3.0)

2.5 (1.5–4.0)

0.0263

MSSSa

2.10 (0.78–5.24)

3.17 (1.16–5.87)

0.0415

1.97 (0.56–5.63)

2.33 (0.88–4.94)

NS

2.28 (1.04–4.97)

4.32 (1.77–6.33)

0.0021

ARRa

0.40 (0.22–0.71)

0.43 (0.22–0.85)

NS

0.40 (0.25–0.71)

0.42 (0.22–0.75)

NS

0.37 (0.17–0.71)

0.48 (0.21–0.95)

NS

Barkhof criteria (%)

113/170 (66.5)

205/258 (79.5)

0.0026

69/92 (75.0)

129/155 (83.2)

NS

44/78 (56.4)

76/103 (73.8)

0.0143

Positive OB and/or increased IgG index (%)

58/129 (45.0)

135/200 (67.5)

<0.0001

41/69 (59.4)

89/108 (82.4)

0.0007

17/60 (28.3)

46/92 (50.0)

0.008

The Mann–Whitney U test was used to compare continuous variables, and the chi-square test was used to compare categorical variables

ARR annualized relapse rate, EDSS Kurtzke’s Expanded Disability Status Scale, MSSS Multiple Sclerosis Severity Score, NS not significant, OB oligoclonal IgG bands, SPMS secondary progressive multiple sclerosis

aMedian (interquartile range)

Comparison of clinical characteristics between HLA-DRB1*15:01-positive and HLA-DRB1*15:01-negative patients

HLA-DRB1*15:01 carriers had a significantly higher frequency of CSF IgG abnormalities than non-DRB1*15:01 carriers (p = 0.0058, Additional file 2: Table S9). The effect of DRB1*15:01 on CSF IgG abnormalities was significant in southern patients, but not in northern patients (p = 0.0002 and p = 0.9042, respectively).

Comparison of clinical characteristics of HLA-DRB1*04:05- or HLA-DRB1*15:01-positive patients between northern and southern Japanese populations

We compared the clinical features of MS patients with the HLA-DRB1*04:05 or HLA-DRB1*15:01 allele between northern and southern Japan, respectively (Table 4 and Additional file 2: Table S10). MS patients with DRB1*04:05 in northern Japan showed higher frequencies of Barkhof brain lesions and positive CSF IgG abnormalities compared with those in southern Japan (p = 0.0105 and p = 0.0004). This suggests that higher latitude increases the frequencies of Barkhof brain lesions and CSF IgG abnormalities independent of the HLA-DRB1*04:05 allele. There were no significant differences between northern and southern Japan in the clinical features of MS patients with the DRB1*15:01 allele.
Table 4

Clinical characteristics of patients with MS and the HLA-DRB1*04:05 allele

 

Northern patients

(n = 92)

Southern patients

(n = 80)

p value

Number of males/females (ratio)

27/65 (1:2.4)

25/55 (1:2.2)

NS

Age (years)a

41 (34–49.5)

36 (28–49)

NS

Age at onset (years)a

27 (21–34)

25 (20–36.8)

NS

SPMS (%)

19/92 (20.7)

7/78 (9.0)

0.035

Disease duration (years)a

10 (6–17)

7.5 (4–14.8)

NS

EDSSa

2.0 (1.0–3.5)

2.0 (1.0–3.0)

NS

MSSSa

1.97 (0.56–5.63)

2.28 (1.04–4.97)

NS

ARRa

0.40 (0.25–0.71)

0.37 (0.17–0.71)

NS

Barkhof criteria (%)

69/92 (75.0 %)

44/78 (56.4 %)

0.0105

Positive OB and/or increased IgG index (%)

41/69 (59.4 %)

17/60 (28.3 %)

0.0004

The Mann–Whitney U test was used to compare continuous variables, and the chi-square test was used to compare categorical variables

ARR annualized relapse rate, EDSS Kurtzke’s Expanded Disability Status Scale, MSSS Multiple Sclerosis Severity Score, OB oligoclonal IgG bands, SPMS secondary progressive multiple sclerosis

aMedian (interquartile range)

Multivariate regression analyses of factors contributing to clinical features and laboratory findings

We adjusted for factors contributing to age at onset, namely geographic region (northern vs. southern), sex, HLA-DRB1*04:05, and HLA-DRB1*15:01. Only the DRB1*04:05 allele was significantly associated with an earlier age at disease onset (p < 0.0001) (Table 5). After adjusting for factors contributing to MSSS, namely geographic region (northern vs. southern), sex, age at onset, MS subtype, ARR, HLA-DRB1*04:05, and HLA-DRB1*15:01, patients living at a higher latitude and with the HLA-DRB1*04:05 allele were independently associated with the lowest quartile of MSSS (adjusted OR = 3.64, p < 0.0001 and adjusted OR = 1.81, p = 0.0266, respectively). Older age at onset, SPMS, and higher ARR were significantly associated with higher MSSS (p = 0.0159, p < 0.0001, and p < 0.0001, respectively). When the logistic regression model for benign MS was used to adjust for the same confounding factors as MSSS, living at a higher latitude and carrying the HLA-DRB1*04:05 allele were significantly associated with benign MS (adjusted OR = 2.63, p = 0.0206; adjusted OR = 2.49, p = 0.0275, respectively), while SPMS had a negative association (p < 0.0001). Results from the multivariate regression analyses for MSSS and benign MS were consistent with these results. Interestingly, MSSS was estimated to decrease by 0.57 per DRB1*04:05 allele (p = 0.0198, Fig. 1), suggesting a gene-dosage effect. A younger age at onset also had a significant positive linear trend with dosage of DRB1*04:05 allele (p = 0.0027). After adjusting for the geographic region (northern vs. southern), sex, age at onset, MS subtype, disease duration, ARR, EDSS, HLA-DRB1*04:05, and HLA-DRB1*15:01, we observed a positive correlation between living at a higher latitude and the presence of Barkhof brain lesions (adjusted OR = 1.63, p = 0.0434) and a negative correlation between HL-DRB1*04:05 and Barkhof brain lesions (adjusted OR = 0.49, p = 0.0043). Additionally, a younger age at onset and SPMS were positively associated with Barkhof brain lesions (p = 0.0132 and p = 0.0384, respectively). Living at a higher latitude also had a strong positive association with positive OB and/or increased IgG index (adjusted OR = 3.80, p < 0.0001). DRB1*04:05 had a strong negative association with CSF IgG abnormalities (and adjusted OR = 0.39, p = 0.0004, respectively) after adjusting for geographic region (northern to southern), sex, age at onset, MS subtype, ARR, EDSS, HLA-DRB1*04:05, and HLA-DRB1*15:01.
Table 5

Multivariate analysis of factors contributing to clinical and laboratory features

Age at disease onset

β

t value

p value

     Region (northern Japan)

−0.0918

−1.94

NS

     Sex (female)

−0.0127

−0.27

NS

      HLA-DRB1*04:05 allele (+)

−0.1970

−4.12

<0.0001

     HLA-DRB1*15:01 allele (+)

−0.0239

−0.50

NS

MSSS (Q1/Q2–Q4)

Adjusted OR

95 % CI

p value

     Region (northern Japan)

3.64

2.15–6.33

<0.0001

     Sex (female)

0.98

0.55–1.76

NS

     Age at onset

0.97

0.95–0.99

0.0159

     SPMS

0.06

0.009–0.20

<0.0001

     ARR

0.15

0.07 − 0.31

<0.0001

     HLA-DRB1*04:05 allele (+)

1.81

1.07–3.07

0.0266

     HLA-DRB1*15:01 allele (+)

1.46

0.83–2.56

NS

Benign MS

Adjusted OR

95 % CI

p value

     Region (northern Japan)

2.63

1.18–6.09

0.0206

     Sex (female)

0.87

0.37–2.00

NS

     Age at onset

0.97

0.94–1.01

NS

     SPMS

0.04

0.008–0.12

<0.0001

     ARR

0.43

0.11–1.42

NS

     HLA-DRB1*04:05 allele (+)

2.49

1.12–5.74

0.0275

     HLA-DRB1*15:01 allele (+)

1.72

0.76–4.04

NS

Barkhof criteria

Adjusted OR

95 % CI

p value

     Region (northern Japan)

1.63

1.01–2.63

0.0434

     Sex (female)

0.80

0.46–1.35

NS

     Age at onset

0.97

0.95–0.99

0.0132

     SPMS

2.55

1.05–6.80

0.0384

     Disease duration (years)

0.98

0.95–1.01

NS

     ARR

1.05

0.67–1.74

NS

     EDSS

0.98

0.85–1.13

NS

     HLA-DRB1*04:05 allele (+)

0.49

0.30–0.80

0.0043

     HLA-DRB1*15:01 allele (+)

1.45

0.85–2.53

NS

Positive OB and/or increased IgG index

Adjusted OR

95 % CI

p value

     Region (northern Japan)

3.80

2.31–6.36

<0.0001

     Sex (female)

1.36

0.78–2.36

NS

     Age at onset

1.00

0.98–1.02

NS

     SPMS

1.43

0.60–3.51

NS

     ARR

0.99

0.66–1.49

NS

     EDSS

1.00

0.87–1.16

NS

     HLA-DRB1*04:05 allele (+)

0.39

0.23–0.65

0.0004

     HLA-DRB1*15:01 allele (+)

1.65

0.95–2.88

NS

Benign MS was defined as an EDSS score  2.0 at least 10 years after disease onset

ARR annualized relapse rate, CI confidence interval, EDSS Kurtzke’s Expanded Disability Status Scale, MSSS Multiple Sclerosis Severity Score, NS not significant, OB oligoclonal IgG bands, OR odds ratio, Q quartile, SPMS secondary progressive multiple sclerosis

Fig. 1
Fig. 1

Copy numbers of HLA-DRB1*04:05 allele and MSSS. MSSS is estimated to significantly decrease by 0.57 per DRB1*04:05 allele (p = 0.0198), with a possible linear dose effect

Discussion

Using multivariate regression analyses, we found that living at a higher latitude and carrying the DRB1*04:05 allele independently lessened the severity of symptoms as evaluated by MSSS. The analyses also revealed that latitude significantly increases the emergence of two hallmarks of MS: fulfillment of the Barkhof criteria for MS, and CSF IgG abnormalities, and that DRB1*04:05 decreases the occurrence of these parameters. The difference in clinical features between northern and southern patients was not simply attributable to the difference in the proportion of SPMS patients enrolled, as even after excluding these patients, the difference remained statistically significant.

Thus, DRB1*04:05 appears to decrease MSSS, the frequency of brain lesions meeting the Barkhof criteria, and CSF IgG abnormalities. This is in accordance with our previous report describing DRB1*04:05-positive MS to be a mild disease with lower frequencies of Barkhof brain lesions and CSF abnormalities [6]. DRB1*04 is also associated with OB-negative MS in a Swedish population [27]. Worldwide, the DRB1*04:05 allele is rare in the general population, but it is one of the most common alleles in some select and isolated populations, such as the Japanese, Sardinians, and Papua New Guineans [28]. DRB1*04:05 is a common susceptibility allele for MS in the Japanese population, and DR4 (DRB1*04:05-DQA1*05:01-DQB1*03:01) is also a susceptibility haplotype for MS in the Sardinian population [29], both of which recently showed a steep rise in MS prevalence [10, 30]. We reported that the proportion of DRB1*04:05 carriers in MS patients rapidly increases with descending year of birth [6]. Thus, DRB1*04:05 is a potential risk factor for MS in the younger generation, which is growing up in a modernized environment. Surprisingly, in our study, DRB1*04:05 had a gene-dosage effect on MSSS, decreasing by 0.57 per DRB1*04:05 allele. Therefore, DRB1*04:05 appears to be unique in its ability to both increase susceptibility to MS and decrease its severity as defined by MSSS. It would be of interest to test whether the bidirectional effects of DRB1*04:05 are observed in other populations, such as Sardinians, in which DRB1*04:05 is a common susceptibility allele.

A higher latitude is known to increase MS risk, and this is also true for the Japanese population [25]. It is notable that among Japanese, latitude also has a strong influence on clinical and laboratory manifestations, being positively associated with fulfillment of the Barkhof criteria for MS and CSF IgG abnormalities, but with less severity MS in patients living in northern Japan. In this study, we also found no significant difference in DRB1 phenotypic frequency between northern and southern controls, suggesting that the observed differences were not likely due to the underlying genetic variation between northern and southern populations. It is interesting to note that latitude also exerts an influence on clinical manifestations in the Japanese population on the mainland with relatively homogeneous HLA backgrounds [31]. In New Zealand, a weak inverse relationship between latitude and disease severity has also been observed [32]. Thus, environmental factors related to latitude are assumed to be more important for producing differences in clinical features than HLA backgrounds.

The effects of latitude are bidirectional; it decreases disease severity as defined by MSSS while increasing the frequencies of Barkhof brain lesions and CSF IgG abnormalities. These bidirectional effects, in part, mask the effects of DRB1*04:05 on MSSS and fulfillment of Barkhof criteria for MS in northern MS patients. SPMS was associated with greater MSSS, but the frequency of SPMS was smaller in the southern MS population than that in the north. This suggests that the greater severity of MS in the south is not related to a chronic progressive phase. After excluding SPMS patients, greater MSSS scores in the southern group than in the northern became more evident in this study. Therefore, the greater MSSS scores in southern MS patients might be related to neuroinflammation during relapse, as well as poor recovery. Total brain T2-weighted lesion load on MRI has little to no correlation with MS disability [33, 34]. However, gray matter atrophy and cortical lesion burdens are the most significant MRI variables correlating with MS disability [35, 36]. In the future, the measurement of brain parenchymal volume and atrophy, as well as the assessment of cortical demyelination using double-inversion recovery MRI images, are required in our cohort to elucidate the factors influencing the differences in MS severity between the two areas. Although we carefully excluded patients with longitudinally extensive spinal cord lesions, spinal cord lesion load and spinal cord atrophy should also be measured in the future. It is important to clarify the effects of latitude on these parameters.

The clinical features of MS in Asians have been reported to be different to those in patients in Western countries. In the fourth nationwide survey in Japan, SPMS was observed in 15.2 % of patients with conventional (classical)-type MS [10], suggesting that SPMS is less common in Japanese patients than in Western patients. It has repeatedly been reported that Japanese patients with MS have low rates of CSF IgG abnormality and Barkhof brain lesions [10, 21, 37]. Some studies have reported that the presence of OB is associated with a worse MS prognosis in Caucasians [38, 39], while others found no significant difference in prognosis between OB-positive and OB-negative MS patients, including a Japanese cohort [27, 37, 40]. We found that neither the presence of Barkhof brain lesions nor CSF abnormalities was associated with MSSS, suggesting that these factors may not be decisive prognostic factors for MS in Japanese populations. We suggest that living at higher latitude might independently exert stronger effects on MS severity than CSF IgG abnormalities. Indeed, this hypothesis is consistent with findings that higher latitude is associated with milder disability in MS patients in New Zealand [32]. Further research is needed to elucidate other factors related to the association of latitude with MS severity in Japanese populations.

In our study, the difference in disease severity in northern patients, as shown by differences in MSSS between DRB1*04:05 carriers and non-carriers, is not as prominent as in southern patients. In southern patients, lower latitude and an absence of DRB1*04:05 increased the median MSSS to 4.33 in the DRB1*04:05 non-carriers. Conversely, in northern patients, higher latitude and the presence of DRB1*04:05 decreased MSSS to 1.97 in DRB1*04:05 carriers. Because the latter value is close to the lower limit, this lowering effect may not be obvious. Alternatively, the effects of latitude might be more potent in DRB1*04:05 non-carriers than in DRB1*04:05 carriers. Further studies are needed to investigate the interactions between the two factors in larger cohorts.

The DRB1*15:01 allele is a strong genetic risk factor for MS in Caucasians and has been associated with earlier age at onset [4] and OB positivity [41]. In the present study, DRB1*15:01 was associated with CSF IgG abnormalities and marginally correlated with fulfillment of the Barkhof criteria for MS. However, these associations lost significance after adjusting for contributing factors. Thus, the effects of DRB1*15:01 on clinical manifestations may be smaller in Asian populations than in European populations.

We also found that DRB1*01:01, DRB1*09:01, DRB1*13:02, and DRB1*15:02 were protective alleles in the Japanese MS population. Based on a meta-analysis, DRB1*09:01 has been reported to be a protective allele for MS in a Chinese population, and this allele is more common in Asians than in other ethnic groups [42]. DRB1*01:01, DRB1*13:02, and DRB1*15:02 have been determined to be novel protective alleles for MS in Japanese populations by the present study. Among the Basque, a Caucasian population living in northern Spain and southwestern France, the DRB1*01:01 allele has a negative association with the disease [43]. The DRB1*15:02-DQB1*06:01 haplotype also decreases the risk for MS in a Sardinian population [44]. Interestingly, DRB1*15:01 and DRB1*15:02 only differ at amino acid position 86 (a valine for DRB1*15:01 and a glycine for DRB1*15:02). The difference of only one amino acid results in opposite effects on MS susceptibility. DRB1*15:01, which contains valine, only tolerates small residues, while DRB1*15:02, which contains glycine, can accommodate large aromatic peptide residues [45]. This small difference may determine the characteristic of presenting antigens, thereby resulting in opposite effects on MS.

Our study has some limitations; first, we did not measure the effects of disease-modifying drugs (DMDs) on clinical course. However, it would be difficult to explain the differences in the clinical manifestations and disease course according to regional and genetic factors based on DMD usage alone as such factors could not be taken into account in the use of DMDs in daily clinical practice. Second, we could not study the interactions between HLA-DRB1 and environmental risk factors because of the small study sample size. The interaction between DRB1*15:01 and environmental risk factors, such as smoking, obesity, vitamin D, and Epstein–Barr virus infection, is well known [4648]; any interaction between DRB1*04:05 and these environmental risk factors remains to be established. Third, although this is the largest study comparing clinical manifestations and genetic backgrounds between patients residing in northern and southern Japan, the sample size was still smaller than in Caucasian MS studies. Nevertheless, we believe it would be valuable to make further regional comparisons of the clinical manifestations and disease courses in genetically and culturally homogeneous populations residing in a wide range of latitudes to shed more light on the possible genetic and environmental influences on neuroinflammation.

Conclusions

Living at a higher latitude and carrying the DRB1*04:05 allele reduces the severity of MS in Japanese MS populations as defined by MSSS. However, both factors influence the frequencies of Barkhof brain lesions and CSF IgG abnormalities in different ways; that is, higher latitudes increase the frequencies of Barkhof brain lesions and CSF IgG abnormalities, whereas DRB1*04:05 decreases them. Further large-scale studies focusing on genetic-environmental interactions are needed to determine the factors associated with the severity of neuroinflammation in MS.

Abbreviations

CI: 

Confidence interval

CSF: 

Cerebrospinal fluid

DMDs: 

Disease-modifying drugs

EDSS: 

Expanded Disability Status Scale

HCs: 

Healthy controls

HLA

Human leukocyte antigen

MS: 

Multiple sclerosis

MSSS: 

Multiple Sclerosis Severity Score

NA: 

Not applicable

NS: 

Not significant

OB: 

Oligoclonal IgG bands

OR: 

Odds ratio

SPMS: 

Secondary progressive multiple sclerosis

Declarations

Acknowledgements

We are grateful to all the participants for providing the blood samples. We are also grateful to the neurologists from JMSGC for providing the DNA samples and clinical information for this study. The JMSGC members are the following: Drs. Yuji Kawano (Site Investigator, Omuta Hospital), Katsuichi Miyamoto (Site Investigator, Kinki University), Susumu Kusunoki (Chairperson, Kinki University), Yuji Nakatsuji (Site Investigator, Osaka University), Hideki Mochizuki (Chairman, Osaka University), Kazuhide Ochi (Site Investigator, Hiroshima University), Masayasu Matsumoto (Chairman, Hiroshima University), Fumitaka Shimizu (Site Investigator, Yamaguchi University), Takeshi Kanda (Chairman, Yamaguchi University), Hirofumi Ochi (Site Investigator, Ehime University), Tetsuro Miki (Chairman, Ehime University), Kazumasa Okada (Site Investigator, University of Occupational and Environmental Health), Sadatoshi Tsuji (Chairman, University of Occupational and Environmental Health), Masami Tanaka (Department Head, Utano National Hospital, National Hospital Organization), Masaaki Niino (Site Investigator, Hokkaido Medical Center, National Hospital Organization), Seiji Kikuchi (Director, Hokkaido Medical Center, National Hospital Organization), Toshiyuki Fukazawa (Director, Sapporo Neurology Clinic), Shin Hisahara (Site Investigator, Sapporo Medical University), Shun Shimohama (Chairman, Sapporo Medical University), Kazuto Yoshida (Deputy Director, Asahikawa Red Cross Hospital), and Hideki Houzen (Department Head, Obihiro Kosei General Hospital). We thank Dr Junji Kishimoto (Centre for Clinical and Translational Research, Kyushu University Hospital, Kyushu University) for his assistance with the statistical analyses.

Funding

This study was supported in part by a Health and Labour Sciences Research Grant on Intractable Diseases (H26-Nanchitou (Nan)-Ippan-074) from the Ministry of Health, Labour, and Welfare, Japan; by the “Practical Research Project for Rare/Intractable Diseases” from Japan Agency for Medical Research and Development, AMED, Japan; and by a Grant-in-Aid for Scientific Research A (MEXT KAKENHI Grant No. 16H02657), a Grant-in-Aid for Scientific Research C (No. 15K09341), a Grant-in-Aid for Exploratory Research (MEXT KAKENHI Grant No. 15K15341), a Grant-in-Aid for Scientific Research on Innovative Areas (No. 25117012), and a “Glial Assembly” Grant-in Aid for Scientific Research on Innovative Areas (JSPS KAKENHI Grant No. 25117001) from the Japan Society for the Promotion of Science, Japan. None of the funding bodies played any role in the study design, data collection and analysis, data interpretation, or writing the manuscript.

Availability of data and materials

The data will be shared on request based on the guidelines of Kyushu University Hospital Ethics Committee.

Authors’ contributions

YN and TM jointly conceived the study, performed the statistical analyses, and wrote the paper. SSa, MN, TF, SY, SH, NI, SSh, MW, KY, HH, YM, RY, and SK participated in the procedure development and collated the data. JK conceived the study, wrote the paper, and supervised this work. All authors reviewed, amended, and agreed on the final version of the manuscript.

Competing interests

TM received a grant and payment from Bayer Schering Pharma and Takeda Pharmaceutical Company for the development of educational presentations and has also received speaker honoraria from Mitsubishi Tanabe Pharma, Bayer Schering Pharma, and Biogen. MN has received funding for travel and/or speaker honoraria from Biogen Idec, Bayer Schering Pharma, Mitsubishi, and Tanabe Pharma Corporation; is part of the scientific advisory board for Biogen Idec; and has received research support from Grants-in-Aid for Scientific Research from the Ministry of Health, Labour and Welfare of Japan. TF serves/has served on scientific advisory boards for Bayer Pharma, Biogen Idec, Mitsubishi Tanabe Pharma Corporation, Takeda Pharmaceutical Company, and Novartis Pharma and has received funding for travel and speaker honoraria from Bayer Pharma, Biogen Idec, Mitsubishi Tanabe Pharma Corporation, and Novartis Pharma. SSh has received speaker honoraria from Novartis Pharma, Boehringer Ingelheim, Kyowa Hakko Kirin, Dainippon Sumitomo Pharma, Takeda Pharmaceutical Company, Daiichi Sankyo Pharma, Jansen Pharma, Eisai Pharma, Biogen Idec, and Mitsubishi Tanabe Pharma Corporation and has received research support from Grants-in-Aid for Scientific Research from the Ministry of Health, Labour and Welfare of Japan and the Smoking Research Foundation. HH serves on scientific advisory boards for Biogen Idec, Novartis Pharma, and Mitsubishi Tanabe Pharma Corporation. JK is a consultant for Biogen Idec Japan and Medical Review; has received honoraria from Bayer Healthcare, Mitsubishi Tanabe Pharma, Nobelpharma, Otsuka Pharmaceutical, and Medical Review; and is funded by a research grant for Nervous and Mental Disorders from the Ministry of Health, Labour and Welfare, Japan, and grants from the Japan Science and Technology Agency and the Ministry of Education, Culture, Sports, Science and Technology, Japan. These sponsors had no control over the interpretation, writing, or publication of this work. YN, SSa, SY, SH, NI, MW, KY, YM, RY, and SK have nothing to declare.

Consent for publication

Not applicable.

Ethics approval and consent to participate

The study received ethical approval from the Kyushu University Hospital Ethics Committee (approval number: 575-03), and written informed consent was obtained from all participants.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Department of Neurology, Neurological Institute, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku Fukuoka, 812-8582, Japan
(2)
Department of Clinical Research, Hokkaido Medical Center, Yamanote 5-jo 7-chome, Nishi-ku Sapporo, 063-0005, Japan
(3)
Sapporo Neurology Clinic, 21-2-1, Kita 21-jo Higashi, Higashi-ku Sapporo, 065-0021, Japan
(4)
Department of Neurology, School of Medicine, Sapporo Medical University, South 1 West 16, Chuo-ku Sapporo, 060-8543, Japan
(5)
Department of Neurology, Asahikawa Red Cross Hospital, 1-1-1, Akebono 1-jo, Asahikawa 070-8530, Japan
(6)
Department of Neurology, Obihiro Kosei General Hospital, 8-1, Nishi 6-jo Minami, Obihiro 080-0016, Japan
(7)
Department of Neurology, Hokkaido Medical Center, Yamanote 5-jo 7-chome, Nishi-ku Sapporo, 063-0005, Japan

References

  1. Trapp BD, Peterson J, Ransohoff RM, Rudick R, Mörk S, Bö L. Axonal transection in the lesions of multiple sclerosis. N Engl J Med. 1998;338:278–85.View ArticlePubMedGoogle Scholar
  2. Ebers G. Environmental factors and multiple sclerosis. Lancet Neurol. 2008;7:268–77. doi:10.1016/S1474-4422(08)70042-5.View ArticlePubMedGoogle Scholar
  3. Lincoln MR, Montpetit A, Cader MZ, Saarela J, Dyment DA, Tiislar M, et al. A predominant role for the HLA class II region in the association of the MHC region with multiple sclerosis. Nat Genet. 2005;37:1108–12.View ArticlePubMedGoogle Scholar
  4. Sawcer S, Hellenthal G, Pirinen M, Spencer CC, Patsopoulos NA, Moutsianas L, et al. Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis. Nature. 2011;476:214–9.View ArticlePubMedPubMed CentralGoogle Scholar
  5. Patsopoulos NA, Barcellos LF, Hintzen RQ, Schaefer C, van Duijn CM, Noble JA, et al. Fine-mapping the genetic association of the major histocompatibility complex in multiple sclerosis: HLA and non-HLA effects. PLoS Genet. 2013;9:e1003926.View ArticlePubMedPubMed CentralGoogle Scholar
  6. Yoshimura S, Isobe N, Yonekawa T, Matsushita T, Masaki K, Sato S, et al. Genetic and infectious profiles of Japanese multiple sclerosis patients. PLoS One. 2012;7:e48592.View ArticlePubMedPubMed CentralGoogle Scholar
  7. Simpson S, Blizzard L, Otahal P, Van der Mei I, Taylor B. Latitude is significantly associated with the prevalence of multiple sclerosis: a meta-analysis. J Neurol Neurosurg Psychiatry. 2011;82:1132–41.View ArticlePubMedGoogle Scholar
  8. Ascherio A, Munger KL. Environmental risk factors for multiple sclerosis. Part II: noninfectious factors. Ann Neurol. 2007;61:504–13.View ArticlePubMedGoogle Scholar
  9. Barkhof F, Filippi M, Miller DH, Scheltens P, Campi A, Polman CH, et al. Comparison of MRI criteria at first presentation to predict conversion to clinically definite multiple sclerosis. Brain. 1997;120:2059–69.View ArticlePubMedGoogle Scholar
  10. Osoegawa M, Kira J, Fukazawa T, Fujihara K, Kikuchi S, Matsui M, et al. Temporal changes and geographical differences in multiple sclerosis phenotypes in Japanese: nationwide survey results over 30 years. Mult Scler. 2009;15:159–73.View ArticlePubMedGoogle Scholar
  11. Dobson R, Ramagopalan S, Davis A, Giovannoni G. Cerebrospinal fluid oligoclonal bands in multiple sclerosis and clinically isolated syndromes: a meta-analysis of prevalence, prognosis and effect of latitude. J Neurol Neurosurg Psychiatry. 2013;84:909–14.View ArticlePubMedGoogle Scholar
  12. Lechner-Scott J, Spencer B, de Malmanche T, Attia J, Fitzgerald M, Trojano M, et al. The frequency of CSF oligoclonal banding in multiple sclerosis increases with latitude. Mult Scler. 2012;18:974–82.View ArticlePubMedGoogle Scholar
  13. Niino M, Sato S, Fukazawa T, Yoshimura S, Hisahara S, Matsushita T, et al. Latitude and HLA-DRB1 alleles independently affect the emergence of cerebrospinal fluid IgG abnormality in multiple sclerosis. Mult Scler. 2015;21:1112–20.View ArticlePubMedGoogle Scholar
  14. Polman CH, Reingold SC, Banwell B, Clanet M, Cohen JA, Filippi M, et al. Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann Neurol. 2011;69:292–302. doi:10.1002/ana.22366.View ArticlePubMedPubMed CentralGoogle Scholar
  15. Wingerchuk DM, Lennon VA, Pittock SJ, Lucchinetti CF, Weinshenker BG. Revised diagnostic criteria for neuromyelitis optica. Neurology. 2006;66:1485–9.View ArticlePubMedGoogle Scholar
  16. Wingerchuk DM, Lennon VA, Lucchinetti CF, Pittock SJ, Weinshenker BG. The spectrum of neuromyelitis optica. Lancet Neurol. 2007;6:805–15.View ArticlePubMedGoogle Scholar
  17. Greer JM. The role of HLA in MS susceptibility and phenotype. Curr Top Behav Neurosci. 2015;26:1–27.View ArticlePubMedGoogle Scholar
  18. Weinshenker BG, Santrach P, Bissonet AS, McDonnell SK, Schaid D, Moore SB, et al. Major histocompatibility complex class II alleles and the course and outcome of MS: a population-based study. Neurology. 1998;51:742–7.View ArticlePubMedGoogle Scholar
  19. Kurtzke JF. Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology. 1983;33:1444–52.View ArticlePubMedGoogle Scholar
  20. Roxburgh RH, Seaman SR, Masterman T, Hensiek AE, Sawcer SJ, Vukusic S, et al. Multiple sclerosis severity score: using disability and disease duration to rate disease severity. Neurology. 2005;64:1144–51.View ArticlePubMedGoogle Scholar
  21. Nakashima I, Fujihara K, Sato S, Itoyama Y. Oligoclonal IgG bands in Japanese patients with multiple sclerosis. A comparative study between isoelectric focusing with IgG immunofixation and high-resolution agarose gel electrophoresis. J. Neuroimmunol. 2005;159:133–6.View ArticleGoogle Scholar
  22. Kira J, Kanai T, Nishimura Y, Yamasaki K, Matsushita S, Kawano Y, et al. Western versus Asian types of multiple sclerosis: immunogenetically and clinically distinct disorders. Ann Neurol. 1996;40:569–74.View ArticlePubMedGoogle Scholar
  23. Kappos L. Placebo-controlled multicentre randomised trial of interferon β-1b in treatment of secondary progressive multiple sclerosis. Lancet. 1998;352:1491–7.View ArticleGoogle Scholar
  24. Pittock SJ, McClelland RL, Mayr WT, Jorgensen NW, Weinshenker BG, Noseworthy J, et al. Clinical implications of benign multiple sclerosis: a 20-year population-based follow-up study. Ann Neurol. 2004;56:303–6.View ArticlePubMedGoogle Scholar
  25. Kira J. Multiple sclerosis in the Japanese population. Lancet Neurol. 2003;2:117–27.View ArticlePubMedGoogle Scholar
  26. Matsushita T, Matsuoka T, Isobe N, Kawano Y, Minohara M, Shi N, et al. Association of the HLA-DPB1*0501 allele with anti-aquaporin-4 antibody positivity in Japanese patients with idiopathic central nervous system demyelinating disorders. Tissue Antigens. 2009;73:171–6.View ArticlePubMedGoogle Scholar
  27. Imrell K, Landtblom AM, Hillert J, Masterman T. Multiple sclerosis with and without CSF bands: clinically indistinguishable but immunogenetically distinct. Neurology. 2006;67:1062–4.View ArticlePubMedGoogle Scholar
  28. González-Galarza FF, Takeshita LYC, Santos EJM, Kempson F, Maia MHT, da Silva ALS, et al. Allele frequency net 2015 update: new features for HLA epitopes, KIR and disease and HLA adverse drug reaction associations. Nucleic Acids Res. 2015;43:D784–8.View ArticlePubMedGoogle Scholar
  29. Marrosu MG, Murru MR, Costa G, Murru R, Muntoni F, Cucca F. DRB1-DQA1-DQB1 loci and multiple sclerosis predisposition in the Sardinian population. Hum Mol Genet. 1998;7:1235–7.View ArticlePubMedGoogle Scholar
  30. Pugliatti M, Sotgiu S, Solinas G, Castiglia P, Pirastru MI, Murgia B, et al. Multiple sclerosis epidemiology in Sardinia: evidence for a true increasing risk. Acta Neurol Scand. 2001;103:20–6.View ArticlePubMedGoogle Scholar
  31. Nakaoka H, Mitsunaga S, Hosomichi K, Shyh-Yuh L, Sawamoto T, Fujiwara T, et al. Detection of ancestry informative HLA alleles confirms the admixed origins of Japanese population. PLoS One. 2013;8:e60793.View ArticlePubMedPubMed CentralGoogle Scholar
  32. Alla S, Pearson JF, Taylor BV, Roxburgh R, Clarke G, Miller DH, et al. An investigation of the relationship between latitude and multiple sclerosis severity in New Zealand. Mult Scler. 2016;22:705–7.View ArticlePubMedGoogle Scholar
  33. Paty DW, Li DK. Interferon beta-1b is effective in relapsing-remitting multiple sclerosis. II. MRI analysis results of a multicenter, randomized, double-blind, placebo-controlled trial. UBC MS/MRI Study Group and the IFNB Multiple Sclerosis Study Group. Neurology. 1993;43:662–7.View ArticlePubMedGoogle Scholar
  34. Lycklama À, Nijeholt GJ, Van Walderveen MAA, Castelijns JA, Van Waesberghe JHTM, Polman C, Scheltens P, et al. Brain and spinal cord abnormalities in multiple sclerosis: correlation between MRI parameters, clinical subtypes and symptoms. Brain. 1998;121:687–97.View ArticleGoogle Scholar
  35. Calabrese M, De Stefano N, Atzori M, Bernardi V, Mattisi I, Barachino L, et al. Detection of cortical inflammatory lesions by double inversion recovery magnetic resonance imaging in patients with multiple sclerosis. Arch Neurol. 2007;64:1416–22.View ArticlePubMedGoogle Scholar
  36. Harrison DM, Roy S, Oh J, Izbudak I, Pham D, Courtney S, et al. Association of cortical lesion burden on 7-T magnetic resonance imaging with cognition and disability in multiple sclerosis. JAMA Neurol. 2015;72:1004–12.View ArticlePubMedPubMed CentralGoogle Scholar
  37. Kikuchi S, Fukazawa T, Niino M, Yabe I, Miyagishi R, Hamada T, et al. HLA-related subpopulations of MS in Japanese with and without oligoclonal IgG bands. Human leukocyte antigen. Neurology. 2003;60:647–51.View ArticlePubMedGoogle Scholar
  38. Avasarala JR, Cross AH, Trotter JL. Oligoclonal band number as a marker for prognosis in multiple sclerosis. Arch Neurol. 2001;58:2044–5.View ArticlePubMedGoogle Scholar
  39. Joseph FG, Hirst CL, Pickersgill TP, Ben-Shlomo Y, Robertson NP, Scolding NJ. CSF oligoclonal band status informs prognosis in multiple sclerosis: a case control study of 100 patients. J Neurol Neurosurg Psychiatry. 2009;80:292–6.View ArticlePubMedGoogle Scholar
  40. Siritho S, Freedman MS. The prognostic significance of cerebrospinal fluid in multiple sclerosis. J Neurol Sci. 2009;279:21–5.View ArticlePubMedGoogle Scholar
  41. Wu J-S, Qiu W, Castley A, James I, Joseph J, Christiansen FT, et al. Presence of CSF oligoclonal bands (OCB) is associated with the HLA-DRB1 genotype in a West Australian multiple sclerosis cohort. J Neurol Sci. 2010;288:63–7.View ArticlePubMedGoogle Scholar
  42. Qiu W, James I, Carroll WM, Mastaglia FL, Kermode AG. HLA-DR allele polymorphism and multiple sclerosis in Chinese populations: a meta-analysis. Mult Scler. 2011;17:382–8.View ArticlePubMedGoogle Scholar
  43. Fernández O, R-Antigüedad A, Pinto-Medel MJ, Mendibe MM, Acosta N, Oliver B, et al. HLA class II alleles in patients with multiple sclerosis in the Biscay province (Basque Country, Spain). J Neurol. 2009;256:1977–88.View ArticlePubMedGoogle Scholar
  44. Cocco E, Sardu C, Pieroni E, Valentini M, Murru R, Costa G, et al. HLA-DRB1-DQB1 haplotypes confer susceptibility and resistance to multiple sclerosis in Sardinia. PLoS One. 2012;7:e33972.View ArticlePubMedPubMed CentralGoogle Scholar
  45. Vogt A, Kropshofer H, Kalbacher H, Kalbus M, Rammensee HG, Coligan JE, et al. Ligand motifs of HLA-DRB5*0101 and DRB1*1501 molecules delineated from self-peptides. J Immunol. 1994;153:1665–73.PubMedGoogle Scholar
  46. Goodin DS. The pathogenesis of multiple sclerosis. Clin Exp Neuroimmunol. 2015;6:2–22.View ArticleGoogle Scholar
  47. De Jager PL, Simon KC, Munger KL, Rioux JD, Hafler DA, Ascherio A. Integrating risk factors HLA-DRB1* 1501 and Epstein–Barr virus in multiple sclerosis. Neurology. 2008;70:1113–8.View ArticlePubMedGoogle Scholar
  48. Hedström AK, Sundqvist E, Bäärnhielm M, Nordin N, Hillert J, Kockum I, et al. Smoking and two human leukocyte antigen genes interact to increase the risk for multiple sclerosis. Brain. 2011;134:653–64.View ArticlePubMedGoogle Scholar

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