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Department of Biomedicine, Aarhus University, Aarhus C, Denmark
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Bioinformatics Research Centre, Aarhus University, Aarhus C, Denmark
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SKAUvaccines, Incuba Science Park, Åbogade 15, DK-8200 Aarhus N, Denmark
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Department of Neurology, Aarhus University Hospital, Aarhus C, Denmark
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Department of Molecular Biology and Genetics, Aarhus University, Aarhus C, Denmark
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Corresponding author
Bjørn A. Nexø
Biomedicine
Aarhus University
Wilhelm Meyers Allé 4
DK-8000 Aarhus C
Denmark email: nexo@hum-gen.au.dk phone: +4587167781 fax: +4586123173
Keywords: Endogenous retrovirus, Multiple Sclerosis, Genetic Association, Human lymphocyte antigen,
HLA, Retroviral expression
Running title: Endogenous retroviruses and HLA in Multiple sclerosis
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Previously, we described the occurrence of multiple sclerosis (MS) to be associated with human endogenous retroviral loci in Danes and Norwegians. Specifically, we found genetic association of MS with the locus HERV-Fc1, located on the X-chromosome. Also, we have recently described that expression of
HERV-Fc1 RNA is approximately 4-fold higher in plasma from MS patients with recent attacks, compared to plasma from patients in a stable state and from controls.
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A conundrum in these studies was the observation that HERV-Fc1 carries two stop-codons and one frameshift in the gag-pol translational unit. Therefore, we speculated that the pol function might be recruited from another viral locus, via either complementation or recombination. We here report that genetic markers near HERV-Fc1 interact statistically with markers in another region in the human genome on chromosome 19, containing the retroviral locus HERV-K13, in promoting MS. Furthermore, we report that markers near HERV-Fc1 and HERV-K13 interact with a tag SNP for the HLA-DRB1*1501 allele in the in the major histocompatibility complex (HLA) in MS. This suggests that the three loci also interact functionally in the disease.
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In a recent paper dealing with a set of genetic epidemiological investigations we described the occurrence of multiple sclerosis (MS) to be associated with human endogenous retroviral loci in Danes. Indirectly, we found association of MS with alleles of the host gene TRIM5 that restricts the replication of a broad variety of retroviruses. Directly, we found genetic association of MS with the endogenous retroviral locus HERV-
Fc1, located on the X-chromosome. The latter association could be reproduced in an additional cohort, and encompassed a total of 1060 cases and 2080 controls [1]. We have later repeated the HERV-Fc1 results in yet another cohort from Norway, encompassing 637 cases and 744 controls [2]. In that study we also showed that one subtype of multiple sclerosis, called Bout Onset MS, was associated with the marker rs391745 near HERV-Fc1, while the rarer Primary Progressive subtype of MS was not, suggesting that the aetiologies of sub-forms of MS differ. Interestingly, an association of Primary Progressive MS with a viral locus on chromosome 7 has been described [3]. Also, we have recently described that expression of HERV-
Fc1 RNA is approximately 4-fold higher in plasma from MS patients with recent attacks, compared to plasma from patients in a stable state and from controls [4], implicating HERV-Fc1 in attacks. Finally, investigations of HIV-positive persons suggest that antiretroviral drugs can curb MS [5, 6].
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A conundrum in our studies was the observation that HERV-Fc1 carries two stop-codons and one frameshift in the gag-pol translational unit; most likely all three mutations are present in pol, but one could be located very late in gag. We therefore speculated that whereas HERV-Fc1 could contribute potential fulllength expression of both gag and env, any pol contribution should be recruited from another virus, via either complementation or recombination, reiterating the notion that endogenous viruses can interact in establishing replication [7-9]. From this, we pursued the notion of statistical interaction between different viruses. The cohort of patients and controls from Aarhus exhibiting the strongest signal for the HERV-Fc1 marker rs391745 was used for the analysis. It contains 350 cases and 540 controls. We here report that in
MS patients in this cohort, markers around HERV-Fc1 interact statistically with another region in the human genome on chromosome 19, containing a retrovirus with a near-open pol element designated HERV-K13.
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Previous reports of reproducible genetic associations in MS have presented data involving the HLA (Human
Leukocyte Antigen) region on chromosome 6 (the human version of the vertebrate major histocompatibility complex (MHC) gene family) [10, 11]. We therefore turned to investigate a potential relation between this immune regulatory region and the proviral elements HERV-Fc1 and HERV-K13. First, to verify the quality of our studies and strengthen the validity of our analysis, we replicated previous established associations between HLA and MS in our cohort. Several single nucleotide variations in genes throughout the HLA region
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83 showed association with MS. Next, we investigated whether any statistical epistatic interaction between
HERV-Fc1 and HLA could be found, underlying a biological interaction between the immune system related region and the endogenous proviruses. We find that a complete 3-way interaction analysis (ANOVA) shows interaction between markers from the regions of HLA, HERV-Fc1 and HERV-K13.
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Blood samples and DNA analysis. The studies were approved by the Science Ethical Committee of the
Central Denmark Region and were performed with informed written consent from all persons. For the DNA analyses, control samples were collected among medical students of Danish extraction at Aarhus
University, and MS patients were recruited at the Department of Neurology, Aarhus University Hospital [1].
All samples were treated identically. Blood was drawn using BD Vacutainer CPT TM tubes and the plasma and peripheral blood mononuclear cells (PBMCs) were isolated and cryopreserved. DNA was purified by conventional means, and the SNPs were genotyped using a Sequenom® platform (San Diego, CA) using conditions as previously described [1]. The SNPs used in the analyses are listed in Table S1.
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Statistics. The genetic data were stored and processed in SPSS (IBM, Armonk, NY). For the ANOVA, we recoded cases and controls as 1 and 0, respectively. We chose the type of ANOVA with a Type III sum of squares for the analysis. Recoding of the SNPs proved unnecessary.
98 Figure 1 was developed in Excel (Microsoft, Richmond, WA).
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We have previously described that the human genome contains approximately 50 endogenous retroviral loci with one or more intact or near-intact genes, i.e. at most two non-lossy breaks (stop codons and frameshifts) in the coding of a gene product (1). We have also described that the locus HERV-Fc1 is associated with MS. Importantly; HERV-Fc1 has a pol region, which is interrupted by one or two stop-codons and a frame-shift. To locate a possible alternative source of pol for HERV-Fc1, we searched the 50 viruses for intact or near-intact pol reading frames. A total of 16 such viruses were found. Interestingly, among these was the virus HERV-K13, present on chromosome 19 at approximate position 22063000 to 22073000 (NCBI
37.1), which had given the next highest association to MS in the initial scan of virus-near markers [1].
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Before analysing for statistical interaction between HERV-K13 and HERV-Fc1, we curated the dataset, including rejecting any SNP with more than 10 percent missing values. SNPs that were monotonous or almost so were also rejected. This brought the dataset down from 303 to 238 SNPs. The remaining SNPs are listed in Table S1. Next, we focused on SNPs near to HERV-K13. A total of 6 such SNPs were found. For these SNPs, we calculated the interaction, measured as the p-value for the product term of each SNP and the HERV-Fc1 marker, rs391745/Fc1, in an ANOVA analysis. Because rs391745/Fc1 is located on the Xchromosome, we used gender-separated ANOVA, and combined the two p-values by Fisher’s method. The data are shown in Table 1.
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Several of the markers near HERV-K13 showed signs of interaction with rs391745/Fc1, most strongly rs2435031/K13 and rs2435029/K13 (p
B
= 0.01 and p
B
= 0.027, Bonferroni corrected p-values). To illustrate the interaction, we have depicted the odds ratios for all nine genotype-combinations of rs2435031/K13 and rs391745/Fc1, calculated against the most common genotype, rs391745/Fc1 GG rs2435031/K13 TT . For simplicity, we pooled men and women and calculated men as homozygous for rs391745/Fc1, although men are really hemizygous for this marker (Figure 1). It is obvious, that while the effect of the risk-genotype, rs2435031/K13 TT rs391745/Fc1 CC is strong, there is only a moderate number of cases with this genotype, but the combined odds ratio for the partial and fully heterozygote carriers is also increased (OR (95%CI) =
1.86 (1.21 – 2.84); p = 0.004).
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In a reciprocal process, we searched for markers in and around HERV-Fc1 that could interact with rs2435031/K13. A total of 43 markers on chromosome X were investigated and the analyses were made as before. The most significant SNP was rs318138/Fc1, giving a p-value for the interaction = 0.0009, which is lower than the value obtained in the previous analysis, with the risk-associated allele being rs318138/Fc1 A .
It is not clear how to correct for the multiplicity of testing in this tiered approach, but it is clear that the set of SNPs showing the highest degree of interaction is rs2435031/K13 and rs318138/Fc1. Table 2 illustrates the complete ANOVA for this combination.
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The human lymphocyte antigens (HLA) have repeatedly been implicated as factors in MS [10].Using a χ 2 analysis we tested 7 HLA SNPs for association with multiple sclerosis in our cohort of western Danes. The
SNPs analysed were scattered throughout the HLA region, covering both class I and class II genes, and most represent variations previously reported in HLA-MS association [11]. 6 out of 7 SNPs showed highly significant association between disease and variation, verifying previous reports and confirming the quality of our data (Table 3). The strongest signal was observed with rs3135388/HLA.
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In an extension of our ANOVA analysis we looked for interaction between HERV markers and markers in
HLA. There was no interaction of HLA markers with either rs391745/Fc1 (gender-separated) or rs2435031/K13 in 2-way ANOVAs. Nor was a gender-separated analysis for interaction between rs318138/Fc1 and rs3135388/HLA positive (results not shown). However, when we made a genderseparated 3-way ANOVA with rs2435031/K13, rs318138/Fc1, and rs3135388/HLA, we found that the pvalue associated with the triple-product term was significant (p = 0.02) and lower than the p-values for the dual-product terms or the single terms for the viruses, indicating that the HLA marker interacts with both viral markers simultaneously. The p-value of the overall model was very low (p = 6*10 -13 ). The analysis is shown in Table S2.
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It is difficult to visualize a 3-way interaction. Instead, we have provided a complete breakdown of cases and controls on the 27 genotypes produced by the program SPSS (Table S3). For simplicity, we treated the males, hemizygous for rs318138/Fc1, as homozygous for this marker. Three genotypes were present containing rs2435031/K13 T rs318138/Fc1 AA rs3135388/HLA T , namely: rs2435031/K13 GT rs318138/Fc1 AA rs3135388/HLA CT , rs2435031/K13 TT rs318138/Fc1 AA rs3135388/HLA CT , and rs2435031/K13 TT rs318138/Fc1 AA rs3135388/HLA TT . The fourth such genotype was not present. Together the three genotypes contained 10 cases and 1 control and had an OR (CI95%) of 34 (4.3 – 275) relative to the most common genotype rs2435031/K13 TT rs318138/Fc1 GG rs3135388/HLA CC .
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As a precaution, we also analysed SNPs near the remaining 15 pol-carrying viruses for interaction with rs318138/Fc1 in MS using a gender-separated ANOVA. Out of 46 SNPs only rs1387153 gave a significant value (p =0.043). Bonferroni correction showed that this could easily be the result of repeated testing (p
B
>
1). Thus, only HERV-K13 candidates as an interaction-partner for HERV-Fc1.
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Moving association studies from single-locus analysis to wider gene interaction analysis seems inevitable in the search for basic etiologic explanations for complex diseases like MS.
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Interaction of endogenous retroviral loci in the establishment of replication and disease has long been known [7-9]. We find it probable that the statistical interaction of the HERV-Fc1 region with the region of chromosome 19, containing HERV-K, is another example of this phenomenon. The specific form of this interaction is unknown. HERV-Fc1 is a gamma-retrovirus, and HERV-Ks are beta-retroviruses and thus relatively distantly related. However, the exchange of ENV proteins occurs readily among even distant
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174 retroviruses and is a definite possibility for HERV-K13 and HERV-Fc1. Recombination between retroviruses depends on the co-packaging of two different viral RNAs into the same particle [12]. Thus, some form of complementation is a prerequisite for recombination. Formation of phenotypically mixed particles has not been investigated in MS.
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None of the viral loci here described as involved in MS were recognized as MS-relevant in a high density genome-wide association study [13]. Perhaps this is due to the fact that SNPs located near or inside retroviral elements are very poorly represented in the predesigned SNP chips used for GWAS studies.
However, the study point to a substantial number of other genes of potential importance for MS, many of which are involved in immune mechanisms. A medium density GWAS using 4804 markers described multiple markers located on chromosome 19 as associated with MS in another Scandinavian cohort [14].
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It is important to emphasize that we have used SNPs as proxies for the viral loci and it is among the SNPs we have found statistical interaction. Although the SNPs are very close to the loci, it remains a possibility that we are observing the effect of other genes close by. Specifically, there is a HERV-H related sequence near HERV-K13. The distance between the two loci on chromosome 19 is so short (17 kb) that we cannot effectively decide by genetic means, which locus interacts with rs391745/Fc1 and rs318138/Fc1, or whether they both do. Although we have no evidence that this HERV-H locus is active, it is noteworthy that
HERV-F and HERV-H are more closely related than HERV-F and HERV-K, and that sero-reactivity towards
HERV-H ENV appears increased in active MS patients [15].
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The 3-way interaction of SNPs near HERV-Fc1, HERV-K13 and HLA strongly suggests that the viral regions are relevant. It is remarkable that such high levels of structure can be detected in a cohort of limited size. It testifies to the close interaction of these regions in the contribution to the development of MS. The actual mechanism by which HERV-Fc1 and HERV-K13 might influence the immune regulation of HLA and eventually affect MS development is still an unanswered question. One possibility is that proviral factors, e.g. antigens mediating molecular mimicry effects, on a background of dysregulated immune factors could trigger an autoimmune response.
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We have recently obtained preliminary genetic evidence that the diseases rheumatoid arthritis and possibly also systemic lupus erythematosus are associated with markers next to endogenous viral loci (Laska et al, unpublished data). Thus, it is possible that we are dealing with a general mechanism in autoimmunity. How the viral loci stimulate the immune system and lead to reactions to self is unclear. One possibility is that the expression of the endogenous loci results in activation of immune mechanisms that normally protect against exogenous retroviral infections [16].
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A recently published case report implied an inhibitory activity of antiretroviral medicines on a specific patient’s MS attacks [5]. Inspired by this, we have investigated the relative risk of MS in a group of persons that were treated with antiretroviral drugs, the HIV-positive patients in Denmark [6]. Although the results were not significant due to a small number of individuals, the results were suggestive of a reduced risk of
MS in these persons. To date, these findings are the best evidence that antiretroviral treatment can curb autoimmunity.
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Our genetic studies of involvement of HERVs in MS are quite new, and waiting to be confirmed independently by other investigators. However, the emerging number of correlations between HERVs and disease in our data strengthens our belief that HERVs play a major role in autoimmune diseases.
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KKN and BAN drafted the manuscript; BH and MJL performed the experiments; PV, MM and BAN performed the calculations; TP provided the blood samples; all authors contributed with ideas, suggestions for the manuscript and literature search.
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1.
Nexø BA, Christensen T, Frederiksen J, Møller-Larsen A , Oturai AB, Villesen P, et al. (2011) The etiology of Multiple Sclerosis: Genetic evidence for the involvement of the human endogenous retrovirus HERV-Fc1. PLoS ONE 6:e16652.
2.
Hansen B, Oturai AB, Harbo HF, Celius EG, Nissen KK, et al. (2011) Genetic association of multiple sclerosis with the endogenous retrovirus HERV-Fc1: Analysis of disease subtypes. PLoS ONE
6:e26438.
3.
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4.
Laska MJ, Brudek T, Nissen KK, Christensen T, Møller Larsen A, et al. (2012) Expression of HERV-Fc1, a human endogenous retrovirus, is increased in patients with active multiple sclerosis J Virol
86:3713-22.
5.
Maruszak H, Brew BJ, Giovannoni G, Gold J. (2011) Could antiretroviral drugs be effective in multiple sclerosis? A case report. Eur J Neurol 18:e110-1.
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Nexø BA, Pedersen L, Koch-Henriksen N, Sørensen HT (2012) Treatment of HIV Infection and Risk of
Multiple Sclerosis: A preliminary population-based cohort study. Epidemiology, in press.
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Cloyd MW, Hartley JW, Rowe WP. (1980) Lymphomagenicity of recombinant mink cell focusinducing murine leukemia viruses. J Exp Med 151:542-52.
8.
Holland CA, Hartley JW, Rowe WP, Hopkins N. (1985) At least four viral genes contribute to the leukemogenicity of murine retrovirus MCF 247 in AKR mice. J Virol 53:158-65.
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Nexø BA, Ulrich K (1983) Variants of type-C retroviruses from DBA/2 mice: protein-structural and biological properties. Virology 125:454-67.
10.
Svejgaard A. (2008) The immunogenetics of multiple sclerosis. Immunogenetics 60:275-86.
11.
Benešová Y, Vašků A, Stourač P, Hladíková M, Fiala A, Bednařík J. (2012) Association of HLA-
DRB1*1501 tagging rs3135388 gene polymorphism with multiple sclerosis. J Neuroimmunol, in press.
12.
Hu WS, Temin HM (1990) Genetic consequences of packaging two RNA genomes in one retroviral particle: pseudodiploidy and high rate of genetic recombination. Proc
Natl Acad Sci U S A 87:1556-60
13.
The International Multiple Sclerosis Genetics Consortium (2007). Risk alleles for multiple sclerosis identified by a genomewide study N Engl J Med 357:851–862.
14.
Jonasdottir A, Thorlacius T, Fossdal R, Jonasdottir A, Benediktsson K, et al. (2003) A whole genome association study in Icelandic multiple sclerosis patients with 4804 markers. J. Immunol. 143:88-92.
15.
Brudek T, Christensen T, Aagaard L, Petersen T, Hansen HJ, et al (2009) B cells and monocytes from patients with active multiple sclerosis exhibit increased surface expression of both HERV-H Env and
HERV-W Env, accompanied by increased seroreactivity. Retrovirology 6:104.
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Nissen KK, Laska MJ, Hansen B, Terkelsen T, Villesen P, et al (2013) Retroviruses and multiple sclerosis – new pieces to the puzzle. Mult Scler., in review.
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Table 1. Statistical interaction between markers near HERV-K13 and rs391745/Fc1. NCBI 37.1.
SNP Position on chromosome 19 1 p(interaction) 2 rs1828453 rs2435031 rs2435029 rs1651559 rs11672223 rs1229931
22055096
22061608
22062158
22074185
22075780
22076150
0.012
0.0017
0.0045
0.04
0.057
0.17
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266
1.
NCBI 37.1
2.
Interaction measured as the p-value for the product term in an ANOVA analysis.
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Table 2. 2-way ANOVA analysis of gender-separated values for rs2435031/K13 and rs318138/Fc1 in MS.
Gender Mean Square F
Female
Male
Combined
Source Type III Sum of squares
6,520 Model
Intercept rs2435031 rs318138
9,395
0.522
1.435 rs2435031*rs318138 2.451
Error 126.784
Total
Corrected total
210.000
133,304
Model
Intercept
5.094
15.992 rs2435031 rs318138
2.459
0.493 rs2435031*rs318138 2.796
Error 71.074
Total
Corrected total
129,000
76.171 rs2435031*rs318138
3
1
2
309
315
314
Degrees of freedom
8
1
2
2
4
566
575
574
5
2
0.815
6.395
0.261
0.717
0.613
0.224
1.019
15.922
1.230
0.493
1.398
0.230
5.346
2.142
6.077
3.638
28.549
1.164
3.203
2.735
4.432
69,220 p-value
0.000
0.000
0.313
0.041
0.028
0.001
0.000
0.005
0.144
0.003
0.0009
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Table 3 . Association of markers near HLA with disease.
HLA marker Position on chrom 6 1 P(association) 2 rs887466 rs4379333 rs9268428 rs2076530 rs3135388 rs2858331 rs151719
31143511
31263751
32344973
32363816
32413051
32681277
32903900
0.009
0.74
0.079
0.0007
1.7*10 -14
0,0004
1.7*10 -6
1.
NCBI 37.3
2.
Χ 2 test for association with MS
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278 rs4971095 rs5920968 rs5962376 rs5993571 rs603486 rs6460216 rs6619307 rs6620400 rs6712285 rs7933855 rs8110756 rs9604952 rs9840472 rs10416706 rs10426414 rs10818593 rs11172544 rs1174600 rs11824690 rs12107596 rs12117797 rs12199776 rs12278842 rs12287199 rs3802981
Table S1. SNPs analysed by Sequenom. rs10266695 rs12261856 rs10985376 rs10985387 rs1152326 rs11523890 rs16926345 rs1939392 rs2091224 rs2136918 rs11754914 rs1249808 rs12611178 rs12823738 rs170320 rs1822077 rs1985254 rs219073 rs2303473 rs281040 rs2984350 rs4618579 rs2182597 rs2984351 rs352697 rs3856908 rs5992338 rs6518591 rs6689503 rs6787835 rs7524742 rs9468414 rs10214511 rs10877101 rs11224962 rs11224968 rs12263936 rs13073918 rs1384625 rs1650930 rs167609 rs2435031 rs281053 rs3740073 rs4148397 rs4805369 rs4809040 rs530133 rs5748485 rs5940190 rs598645 rs6620397 rs6791696 rs7253937 rs7254577 rs7650483 rs1229931 rs1828453 rs2435029 rs8182505 rs9604911 rs10232215 rs10792346 rs11092162 rs12925045 rs1564653 rs1651576 rs2140336 rs2504278 rs2652427 rs2688228 rs2902299 rs322119 rs3872610 rs4132355 rs4517316 rs4679676 rs4679677 rs5983521 rs6451123 rs6460219 rs7650656 rs819079 rs10403221 rs11264397 rs11760888 rs12185748 rs12196881 rs12934809 rs1387153 rs1651559 rs219200 rs2631731 rs3088174 rs4576878 rs4686378 rs4717229 rs4718180 rs17333695 rs318129 rs318131 rs11085338 rs12013135 rs318155 rs5962377 rs6619299 rs7109277 rs7886111 rs9394742 rs11092163 rs11646366 rs11672223 rs12845339 rs16894097 rs318133 rs421531 rs4786303 rs4786305 rs4786309 rs628526
rs1548293 rs2779642 rs4786304 rs4974767 rs5920969 rs618561 rs6419443 rs6431123 rs6817808 rs71534260 rs71539636 rs71539637
rs34400779 rs36019431 rs55802271 rs73260457 rs12971429 rs2125324 rs400586 rs4827909 rs4727276 rs4764383 rs5983522 rs6501089 rs6620396 rs7586085 rs9819214 rs11797742 rs11882251 rs12192983 rs1249822 rs16889290 rs1929761 rs2096537 rs219077 rs219078 rs2347214 rs2652425 rs4238842 rs545075 rs5748489 rs7288876 rs9393931 rs10426848 rs1152324 rs1929772 rs2189362 rs2379168 rs2396212 rs318132 rs318136 rs318156 rs318157 rs445913 rs5964961 rs6615516 rs6619304 rs7116792 rs7935912 rs318138 rs387312 rs391745 rs318134 rs318190 rs35072987 rs5916942 rs6540338 rs6752853 rs6781014 rs6907006 rs73199783 rs7891183 rs6419444 rs9874803 rs5750717 rs6001376 rs2142833 rs9607600 rs2413570 rs151719 rs2076530 rs2858331 rs3135388 rs4379333 rs887466 rs9268428 rs1498553
rs55748203 rs56753401 rs1332885 rs1332886 rs17305868 rs318158 rs318162 rs318166 rs318168 rs318173 rs3824949 rs5916943
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Table S2. 3-way ANOVA analysis of gender-separated values for rs2435031/K13, rs318138/Fc1 and rs3135388/HLA in
MS.
Gender Source Type III
Sum
Of Squares
Degrees of
Freedom
Mean
Square
F p-value
Male
Female Corrected Model
Intercept rs2435031 rs318138 rs3135388 rs2435031*rs318138 rs2435031*rs3135388 rs318138*rs3135388 rs2435031*rs318138*rs3135388
Error
Total
Corrected Total
Corrected Model
Intercept rs2435031 rs318138 rs3135388 rs2435031*rs318138 rs2435031*rs3135388 rs318138*rs3135388 rs2435031*rs318138*rs3135388
Error
Total
Corrected Total
Combined rs2435031*rs318138*rs3135388
16.236
6.995
0.735
0.102
0.179
1.334
1.954
1.719
1.781
110.758
202.000
126,993
13.060
13.074
1.008
0.499
2.549
1.198
1.159
0.144
0.610
59.655
122.000
72.715
523
544
543
14
1
2
1
2
4
4
3
3
20
1
2
2
2
2
4
2
1
287
302
301
0.812 3.833 0.000
6.995 33.031 0.000
0.367 1.735 0.177
0.051 0.240 0.787
0.089 0.422 0.656
0.333 1.574 0.180
0.488 2.306 0.057
0.573 2.705 0.045
0.594 2.803 0.039
0.212
0.933 4.488 0.000
13.074 62.898 0.000
0.504 2.425 0.090
0.499 2.399 0.122
1.275 6.132 0.002
0.599 2.882 0.058
0.290 1.394 0.236
0.072 0.346 0.708
0.610 2.934 0.088
0.208
0.02
14

Table S3. Number of cases and controls in all 27 genotypes.
Hemizygotic males rubrizised as homozygotes for rs318138.
Count rs2435031 rs3135388
GG
GT
TT
CC state control case
Total
TC state control case
Total
TT state control case
Total
Total state control case
Total
CC state control case
Total
TC state control case
Total
TT state control case
Total
Total state control case
Total
CC state control case
Total
TC state control case
Total
TT state control case
Total
Total state control
AG
3
4 rs318138
GG
36
11
1
4
7
3
33
12
22
205
124
329
161
47
208
81
137
51
188
58
61
119
10
57
53
110
8
11
19
226
1
2
3
48
47
11
20
31
29
13
4
17
7
22
0
1
12
1
3
9
11
3
13
16
13
0
7
6
2
2
20
6
5
AA
4
0
4
0
1
1
1
4
5
6
10
1
4
6
1
1
5
0
2
4
1
0
5
5
1
5
5
4
Total
22
36
1
2
43
15
58
14
3
58
39
12
23
216
152
368
175
56
231
97
144
65
209
61
75
136
11
65
63
128
8
14
22
248
15

304
305
306
307
Total case
Total
CC state control case
Total
TC state control case
Total
TT state control case
Total
Total state
Total control case
126
134
260
19
111
337
334
109
443
25
44
479
268
747
13
16
29
1
12
32
19
21
40
33
39
2
3
72
140
160
300
20
133
381
362
136
498
28
48
522
324
846
1
10
11
0
10
12
9
6
15
10
17
1
1
27
16

312
313
314
315
316
317
318
319
320
321
322
308
309
310
311
Figure 1. Odds ratios of MS for genotype combinations of rs2435031/K13 and rs391745/Fc1 1,2 .
The columns indicate the odds ratios, the numbers above the number of cases and controls.
1.
Men were calculated as homozygous. Odds ratios were calculated against rs2435031/K!3
TT rs391745/Fc1 GG
2.
p-value for rs2435031/K13 TT rs391745/Fc1 CC = 0.00003; p-value for rs2435031/K13 GT rs391745/Fc1 CG = 0.0003
17