Human Molecular Genetics, 2002, Vol. 11, No. 19 2251-2256
© 2002 Oxford University Press
Multiple susceptibility loci for multiple sclerosis
1Program in Human Genetics, Vanderbilt University Medical Center, Nashville, TN 37232, USA, 2Center for Human Genetics, Duke University Medical Center, Durham, NC 27710, USA and 3Department of Neurology, University of California, San Francisco, CA 94143, USA
Received April 18, 2002; Accepted July 5, 2002
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONRESULTSDISCUSSIONMATERIALS AND METHODSREFERENCES |
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Multiple sclerosis (MS) is a common and frequently disabling autoimmune disorder mediated by autoaggressive T cells and autoantibodies that target central nervous system myelin. While numerous studies have demonstrated a strong genetic component to MS, it has been difficult to identify the specific genes involved. Several genomic screens have been undertaken to locate such genes, but have not provided consistent gene localization, except for the MHC on chromosome 6p21 and a locus on chromosome 19q13. To determine which of the original genomic locations presented in the US genome screen could be replicated, a more detailed analysis of additional families was performed. The results, derived from a population of 266 affected individuals belonging to 98 multiplex families, continue to support linkage to chromosomes 6p21, 6q27, and 19q13 with LOD scores>3.0, and suggest that regions on chromosomes 12q23–24 and 16p13 may also harbor susceptibility loci for MS. Analysis taking into account the known HLA-DR2 association identified two additional potential linkage regions on chromosomes 7q21–22 and 13q33–34. These regions can now be targeted for detailed study to identify the underlying MS susceptibility genes.
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONRESULTSDISCUSSIONMATERIALS AND METHODSREFERENCES |
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Multiple sclerosis (MS) is a chronic immune-mediated demyelinating disease of the central nervous system and a frequent cause of acquired neurologic disability beginning in early or middle adult life. The genetic etiology of MS has been studied for many years, but, owing to the complex and likely oligogenic etiology of the disease, there have been few successes in uncovering the underlying genes. Twin studies, half-sibling studies and adoption studies have all suggested a strong genetic component in MS (1–4), yet linkage, association and candidate gene studies have found few reproducible targets for MS susceptibility genes. Only one site, the major histocompatibility complex (MHC) [in particular the HLA-DR2 (*1501) allele] on chromosome 6p21, has consistently been confirmed in linkage and case–control studies as being associated with MS (5). However, the mechanism by which the MHC affects MS is still unknown. Ultimately, the remaining MS genes must be found in order to better treat, understand and possibly prevent this debilitating disease.
Even as the human genome sequencing is finished and the scientific community begins the laborious process of understanding the 30 000–50 000 genes contained therein, genome screens still serve as an efficient and workable method to locate disease genes without prior bias. Numerous genomic screens searching for the genetic components to MS have been reported (6–11). The Multiple Sclerosis Genetics Group (MSGG) used 52 families (126 affected relative pairs) from the USA to identify 19 potential regions, with the strongest results being in the HLA region and on chromosome 19q (6). 129 families (143 affected sib pairs) from the UK were screened, and 19 regions were identified, with the strongest results being near the MHC and on chromosome 17q22 (7). Sixty-one families (100 affected sib pairs) from Canada were screened, and 5 regions were identified, with the strongest results being on chromosome 5p (9). Sixteen large Finnish pedigrees (30 affected sib pairs) were screened, and 10 regions were identified, with the strongest results being on chromosome 17q22–24 (8). Forty-nine Sardinian families (55 affected sib pairs) were screened, and 10 regions were identified, with the strongest results being on chromosomes 1q, 10q and 11p. Forty Italian families (40 affected sib pairs) were screened, and 3 regions were identified, with the strongest results being on chromosomes 1cen, 5q and 15 (10,11). The present report provides analysis of a larger data set for the 19 regions originally described by the US group (6).
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RESULTS |
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TOPABSTRACTINTRODUCTIONRESULTSDISCUSSIONMATERIALS AND METHODSREFERENCES |
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The peak two-point scores for each region are summarized in Table 1. Only regions on chromosomes 6p21, 6q27, 12q23–24, 16p13 and 19q13 met our primary criterion (overall LOD score >2.0) for further interest. In each of these regions, the evidence of linkage came from both tier 1 (the original 52 families) and tier 2 (the follow-up 46 families), with LOD scores >0.65 in each tier. Multipoint analyses resulted in very similar results. None of the other regions generated interesting LOD scores.
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Taking into account the known HLA-DR2 association (Tables 2 and 3), the use of two stratification approaches demonstrated that the results on chromosomes 6p21 seemed to arise mostly in the HLA-DR2+ families, as expected based on the known HLA-DR2 association. The linkages for 6q27, 12q23–24 and 16p13 are not as clear, since positive LOD scores were found in all HLA-DR2 strata, with the strongest results coming from the HLA-DR2+, HLA-DR2+ and non-HLA-DR2+ families, respectively. Stratification identified two additional regions with suggestive linkage on 7q21–22 and 13q33–34 (Tables 2 and 3). The chromosome 7q21–22 linkage was observed only in the HLA-DR2- families (HLOD=2.21, MLS=1.95). The chromosome 13q33–34 linkage was observed only in the HLA-DR2+ families (HLOD=2.17, MLS=2.10). These results hold true in the overall dataset as well as within each tier.
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The multipoint results weighted by HLA-DR2 status were, in general, similar. Chromosomes 6p21 and 13q33–34 had stronger LOD* scores when the families were weighted by the number of HLA-DR2+ individuals (3.76 and 2.03, respectively). Chromosomes 7q21–22 and 16p13 had stronger LOD* scores when the families were weighted by the number of HLA-DR2- individuals (0.39 and 2.36, respectively). The other three regions (6q27, 12q23–24, and 19q13) had similar scores regardless of the weighting scheme.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONRESULTSDISCUSSIONMATERIALS AND METHODSREFERENCES |
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The initial study of 52 US multiplex MS families identified 19 regions that might harbor MS susceptibility loci. More detailed examination of these regions using an expanded dataset containing both the original 52 and a new set of 46 families has demonstrated the continued possibility of MS susceptibility loci for only five of these regions: 6p21, 6q27, 12q23–24, 16p13 and 19q13. Three of these regions (6p21, 6q27 and 19q13) generated LOD scores >3, while two others (16p13 and 12q23–24) generated LOD scores >2.4.
Little needs to be said about the strong results for the MHC. This has been seen in virtually every dataset examined (6–11), and confirms the known HLA-DR2 association. The strongest evidence of an MS locus outside of the MHC was for the 6q27 region (HLOD=3.29). This region was also identified in the UK genomic screen and follow-up (7,12,13) as well as in a Swedish population (12), but not in the Canadian or Finnish screens or their follow-up datasets (8,9,14).
The regions near 12q23–24, 16p13 and 19q13 have been examined in multiple datasets. 12q23–24 was tested in the Swedish dataset, with additional positive results (12), and was also seen in the Canadian follow-up analysis (14). However, the French Multiple Sclerosis Genetics Group (15) did not to find significant linkage, nor did analysis of the Finnish and UK samples (8,13). The current results for chromosome 16p13 are at odds with both the Swedish and French studies (12,15) as well as the British and Canadian studies. 19q13 has been examined in detail elsewhere (16), but numerous positive results, both for linkage and association, have been seen in this region (6–9,17–20).
The known linkage to the MHC and association with the HLA-DR2 allele could make the identification of other regions more difficult. This has been shown in type 2 diabetes, where a locus on chromosome 2 was identified only after weighting the analyses for linkage to another locus (21). Performing a similar analysis on these data was revealing. Two additional regions were identified (chromosomes 7q21–22 and 13q33–34) whose linkage was most strongly seen when weighting the HLA-DR2 allele more (13q33–34) or less (7q21–22) heavily. In the other four non-MHC regions, weighting revealed that most of the linkage information for 16p13 arose when weighting the HLA-DR2 less heavily, while the results for the other three regions (6q27, 12q23–24 and 19q13) seemed largely unaffected by weighting. These results imply effects independent of HLA-DR2 for 7q21–22 and 16p13, and possible interactive effects for a locus on chromosome 13q33–34.
Two methods were applied to the data to account for the possible effect of the HLA-DR2 association. Stratification is simple to apply, but potentially suffers from reduced sample sizes in each subgroup, as seen here where the number of families without any individuals carrying an HLA-DR2 allele is only 24 (
25% of the entire dataset). An alternative approach is to weight each family by the presence or absence of the HLA-DR2 allele. This allows the use of the entire dataset for all analyses. Perhaps surprisingly, both methods provided similar results.
Linkage analysis in complex traits has proven more difficult than first suggested (22). One prominent problem has been the inconsistency between studies, with few regions in common. For example, while >70 regions were identified in the initial four MS genomic screens (6–9), only 11 could be considered in common across even two groups. This should not be particularly surprising, since genomic screens are generally designed to detect true loci while accepting a high false-positive rate. Critical to this method is replication in additional datasets. We have completed a further analysis of US families, and have identified seven regions, five of which (6p21, 6q27, 7q21–22, 12q23–24 and 19q13) have also been seen in at least one, and sometimes several, other datasets. Thus, the next step is to investigate these five regions in more detail to more carefully localize the linkage signal and identify the underlying susceptibility gene(s).
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONRESULTSDISCUSSIONMATERIALS AND METHODSREFERENCES |
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Families
Families were ascertained by the University of California at San Francisco (UCSF) team through physician referrals, self-referrals and responses to advertisements. Positive family histories were investigated by direct contact with other family members, requests for medical records, and by clinical examination, laboratory testing or paraclinical studies (MRI scanning and evoked-response testing). All affected family members were examined or had their medical records reviewed by one of the authors (S.L.H.). Consistent and stringent clinical criteria were applied as previously described (6,23). Individuals were placed into one of four categories: definite MS, probable MS, possible MS and no evidence of MS. Only definite MS individuals were considered as affected in the analyses. Families were extended through all affected first-degree relatives if possible. The appropriate institutional review boards approved all studies, and informed consent was obtained from all participants.
The families consisted of 52 multiplex families (tier 1) that were collected prior to and then used for the original genomic screen (6). These families [386 individuals; 135 affecteds, 72 affected sib pairs (ASPs) and 54 other affected relative pairs (ARPs)] were genotyped for all the new markers. 46 new families (tier 2) (336 individuals; 131 affecteds, 99 ASPs and 37 other ARPs) were collected as a follow-up dataset to further investigate linkage in the interesting regions identified from the screen (Table 4).
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DNA analysis
Blood samples were collected after informed consent, and lymphoblastoid cell lines were initiated on all samples (24). DNA was extracted using standard procedures. Genotyping of the microsatellite markers utilized a semi-automated fluorescence scanning system (FAAST, Duke University) (25), silver staining (Vanderbilt University) (26) and automated fluorescence scanning (UCSF). The tested markers and their relative map positions are given in Table 5. Markers were chosen to generate a more densely mapped region surrounding the markers that gave significant results in the original genomic screen. Markers were also chosen with a preference for high heterozygosity and ease of genotyping. Genotypes for HLA-DR were determined at UCSF using a non-radioactive PCR–SSOP (Dynal, Norway). Regions surrounding 6p21 and 19q13 are being studied intensively, as described in more detail elsewhere (16,27). Marker orders were determined using genetic linkage reference maps (http://research.marshfieldclinic.org/genetics/ ). Where order was undetermined, the human genome sequence was used to determine order (www.ncbi. nih.gov). Each laboratory had a complete set of DNAs, and each laboratory was assigned a subset of markers to genotype. In producing genotypes, laboratory staff was blinded to pedigree structure and to clinical status of family members.
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Linkage analysis
Prior to linkage analysis, all data for the 19 follow-up regions underwent a lengthy process of error detection and genotype confirmation. The initial step in error detection was testing for simple Mendelian inheritance inconsistencies using PEDCHECK (28). These potential errors were reviewed, and genotype corrections were made when errors were found. The second step was to test for unlikely double recombinations within each of the follow-up regions. SIMWALK v2.0 (28) was used to haplotype all genotyped individuals. The laboratory reviewed specific markers in specific families that showed double recombinations, and genotype corrections were made when errors were found. If apparent double recombinations were confirmed in multiple readings, the marker data remained in the dataset.
The data were analyzed for linkage using genetic model-based and model-free methods. Two-point LOD scores for both autosomal dominant and recessive models were calculated using two models. Model 1 assumed autosomal dominant inheritance with an MS disease allele frequency of 0.05. Model 2 assumed autosomal recessive inheritance with an MS disease allele frequency of 0.20 (6). Both models used phenotypic information on only affected individuals. All LOD scores were calculated with FASTLINK (29). Heterogeneity LODs were then calculated for both autosomal dominant and recessive results using HOMOG (30), and the maximal score was reported as an HLOD. For model-free testing of linkage based on ASPs, we used the ASPEX package (31) to calculate both two-point and multipoint MLS. Further multipoint model-free testing was conducted with ALLEGRO (32). ALLEGRO uses ARP data to compute an allele-sharing LOD* score, based on an exponential model that uses the Spairs scoring function as recommended by McPeek (33). Owing to computational limitations of the ALLEGRO software, some large pedigrees were trimmed to conduct the analysis. Given the original criterion of a LOD score 
1.0 (6) and the approximate doubling of the dataset, a LOD score of 2.0 was chosen as the criterion for continued interest.
The effect on other potential loci of the known HLA-DR2 association with MS was tested using both stratification and conditional weighting. The first approach stratified the 98 families in two ways: (i) a contrast of families where all affected individuals carried an HLA-DR2 allele (53 families, DR2+) against all remaining families (45 families); (ii) a contrast of families where none of the affected individuals carried an HLA-DR2 allele (24 families, DR2-) against all other families (74 families). A second approach used a weighted multipoint LOD* score based on the proportion of affected family members who carried the HLA-DR2 allele.
Allele frequencies were estimated from genotypic information derived from all unrelated individuals in the combined dataset, consisting of over 100 chromosomes. These allele frequencies were compared with available data from other Caucasian populations, and no significant differences were observed (data not shown). The LAPIS program of the PEDIGENE system (34) was used to produce the necessary analysis files for the different programs.
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ACKNOWLEDGEMENTS |
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We thank the patients and their families, without whom this study would not have been possible, The Duke Center for Human Genetics database personnel, and Annie Bernard for help with the manuscript preparation. This work was supported by grants from the National Multiple Sclerosis Society (NMSS) (S.L.H. and J.R.O.), NIH Grants NS32830 (J.L.H. and M.P.-V.) and NS26799 (S.L.H.), the Mathers Foundation (S.L.H.), and the Nancy Davis Foundation (S.L.H.).
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FOOTNOTES |
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* To whom correspondence should be addressed at: Program in Human Genetics, 519 Light Hall, Vanderbilt University Medical Center, Nashville, TN 37232-0700, USA. Tel: +1 6153438555; Fax: +1 6153438619; Email: jonathan{at}phg.mc.vanderbilt.edu
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REFERENCES |
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