Human Molecular Genetics, 2002, Vol. 11, No. 19 2257-2267
© 2002 Oxford University Press
Fine mapping of a multiple sclerosis locus to 2.5 Mb on chromosome 17q22–q24
1Department of Human Genetics, UCLA School of Medicine, Los Angeles, CA, USA, 2Department of Molecular Medicine, National Public Health Institute, Finland, 3Department of Obstetrics and Gynecology, ColumbiaUniversity, NY, 4Department of Neurology, University of Helsinki, Neuroscience Programme, Biomedicum-Helsinki, Haartmaninkatu 8, PL700, Helsinki, Finland, 5School of Public Health, University of Tampere, Tampere, Finland, 6Department of Neurology, Tampere University Hospital, Tampere, Finland, 7Central Hospital of Seinäjoki,Seinäjoki, Finland, 8Department of Neurology and Neuroscience, Kuopio University Hospital, Kuopio, Finland, 9Department of Neurology, Oulu University Hospital, Oulu, Finland and 10Department of Medical Genetics,University of Helsinki, Finland
Received April 24, 2002; Accepted July 5, 2002
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONRESULTSDISCUSSIONMATERIALS AND METHODSREFERENCES |
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Genome-wide linkage analyses performed in a Finnish study sample have identified four potential predisposing loci for multiple sclerosis (MS). Here we made an effort to restrict the wide linkage region on chromosome 17 with a dense set of 31 markers using multipoint linkage analyses and monitoring for shared marker alleles in MS chromosomes. We carried out the linkage analyses in 22 Finnish multiplex MS families originating from a regional subisolate that shows an exceptionally high prevalence of MS in order to minimize the genetic and environmental heterogeneity of the study sample. Thirty markers on the 23 cM initial interval gave positive pairwise LOD scores. We monitored for shared haplotypes among affected family members within a family, and identified an
4 cM region flanked by the markers D17S1792 and ATA43A10 in 17 out of the 22 families (77.3%). The multipoint linkage analyses using Genehunter and SIMWALK 2.40 provided further evidence for the same 4 cM region, for example a maximal multipoint NPL score of 5.98 (P<0.0002). We observed nominal evidence for association to MS, with one marker flanking the shared region, and this association was replicated in the additional set of families. Using the combined power of linkage, association and shared haplotype analyses, we were thus able to restrict the MS locus on chromosome 17q from 23 cM to a 4 cM region covering a physical interval of 2.5 Mb. Thus, this study describes the restriction of an MS locus outside the HLA region into a segment approachable by molecular tools. |
INTRODUCTION |
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TOPABSTRACTINTRODUCTIONRESULTSDISCUSSIONMATERIALS AND METHODSREFERENCES |
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Multiple sclerosis (MS) is a chronic neurological disorder characterized by multicentric inflammation, demyelination and axonal damage (1,2) resulting in heterogeneous clinical features, including pareses, sensory symptoms and ataxia. The classical clinical features include disturbances in sensation and mobility. The typical age of onset is between years 20 and 40, making MS one of the most common neurological diseases of young adults. The highest incidence (2–4/105) and prevalence (50–100/105) of MS have been reported in populations of northern European descent living in temperate climate (3). In Finland, distinctly higher incidence (12/105) and prevalence (200/105) rates have been recently documented in the Southern Ostrobothnian healthcare district of Seinäjoki (4,5). This region also shows exceptional familial clustering of MS (6). The etiology of MS is still unknown, but the epidemiological studies, as well as twin and adoption studies, suggest significant genetic predisposition (7–11). Four genome-wide scans have revealed several putative susceptibility loci, of which the loci on chromosomes 6p, 5p, 17q and 19q have been replicated in multiple study samples (12–16).
In our genetic studies of MS, we have taken advantage of the isolated Finnish population, with well-established genealogical registers (17,18). The restricted number of founders, especially in regional subisolates, as well as environmental and cultural homogeneity, are features that make the Finnish population potentially very useful in genetic studies of complex diseases (19). Previous linkage analyses performed in the Finnish study sample have identified four main candidate regions for MS: the HLA locus on chromosome 6, the MBP locus on chromosome 18 and two relatively wide regions on chromosomes 5p12–p14 and 17q22–q24 (15,20–23). Interestingly, the locus on chromosome 17 has been implicated for linkage to MS in other genome scans from more heterogeneous populations (14,16,24). Further, this locus is syntenic to the rat experimental allergic encephalomyelitis (Eae) locus on rat chromosome 10 (25), and to the initially reported mouse Eae7 locus on chromosome 11 (26). However, recent fine mapping of the mouse locus restricted the quantitative locus on mouse chromosome 11 from a 23 cM to an 8 cM interval, making the overlap between human and mouse loci non-existing (27).
Here we have made an effort to restrict the wide susceptibility locus on chromosome 17q22–q24 to a region that could be analyzed with molecular tools. To minimize the genetic and environmental heterogeneity, this restriction effort focused on families originating from the high-risk region of Southern Ostrobothnia with increased familial occurrence of MS disease. In this study, we established a physical map over the critical region, covered it with multiple markers, and used the combined power of linkage and association analysis as well as haplotype sharing of MS chromosomes to define the critical region to 2.5 Mb.
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RESULTS |
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TOPABSTRACTINTRODUCTIONRESULTSDISCUSSIONMATERIALS AND METHODSREFERENCES |
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Fine mapping of the chromosome 17 region
To restrict the relatively wide region on chromosome 17q22–q24 showing evidence for linkage to MS, we genotyped a total of 31 markers mapping to this 23 cM region. To minimize the genetic and environmental heterogeneity in our study sample, we performed the fine mapping in 22 large pedigrees originating from Southern Ostrobothnia, an internal isolate on the western coast of Finland with an exceptionally high prevalence and familial occurrence of MS (Fig. 1: set 1a). Two-point LOD scores were calculated using the MLINK program (28,29), adopting a dominant model of inheritance and a low penetrance value (0.05), thus extracting linkage information only from the affected individuals and using the genotypes of unaffected family members only for phase information. Thirty markers gave positive maximum pairwise LOD scores; the highest were obtained with the markers D17S1825 (3.68,
=0.0), D17S1302 (2.84, =0.05), D17S807 (2.52, =0.05) and D17S1290 (2.52, =0.05) (Table 1). To ensure that our findings were not specific to this exceptional subpopulation, the critical markers were also genotyped in the other six large pedigrees originating from other parts of Finland (Fig. 1: set 1b). All six tested markers gave positive, and half even slightly higher maximum, LOD scores in the entire sample set 1 (Table 2), indicating that families from other parts of Finland also contributed to the LOD scores, although most of the linkage information emerged from the families originating from the subisolate.
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Construction of the physical map
To be able to construct marker haplotypes and to carry out multipoint analyses, we needed to define the precise order of the markers and the genetic distances between them. We used multiple approaches, including PCR of the large insert YAC/BAC/PAC clones, radiation hybrid mapping and computer-assisted sequence comparisons of fully and partially sequenced clones in NCBI and Celera databases, to create an integrated physical map over the 23 cM region on 17q22–q24. This order was further verified by multicolor FISH with 10 clones to normal and mechanically stretched metaphase chromosomes. The obtained order of markers used for linkage and haplotype analysis agreed best with the Celera map (Fig. 2).
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Haplotype sharing among affected family members
We constructed chromosomal haplotypes in multiplex MS families by the SIMWALK 2.40 program (30) using genotypes of 23 markers spanning a 23 cM region between D17S956 and D17S2182. The haplotypes were monitored for sharing in the MS alleles of 22 families originating from the high-risk region of Southern Ostrobothnia.
Although we were not able to find any single haplotype shared by all MS alleles, in 17 out of the 22 families (77.3%) an 4 cM region of chromosome 17 flanked by the markers D17S1792 and ATA43A10 was systematically shared by all the affected individuals within each family (Fig. 3). The same haplotypes were also observed on average in 35% of the unaffected family members. The affected individuals of the remaining 5 families did not share any part of the haplotype on chromosome 17 (Fig. 3).
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2 affected sibs; p-o, parent+offspring(s); one, DNA of one affected person was available.To monitor for sharing of alleles in a larger set of MS chromosomes, we genotyped the six markers mapping within and flanking the putative 4 cM susceptibility region (D17S1825, D17S1874, D17S807, D17S1813, ATA43A10 and D17S789) in six multiplex and 167 trio families (Fig. 1: sets 1b and 2, respectively). Additionally, 250 new single affected MS families (Fig. 1: set 3) were collected and the six markers were genotyped. Haplotypes were constructed with Simwalk 2.40 (30) in these 423 families using the genotypes of the six critical markers.
First, we monitored sharing of chromosome 17 haplotypes in the additional six multiplex families originating from central and southern Finland. We observed that the 4 cM DNA region flanked by the markers D17S1792 and ATA43A10, shared by the MS patients of the families originating from the high-risk region, was also shared by the affected individuals in five of the six multiplex families originating from the other parts of Finland. Second, we constructed two-marker haplotypes with the marker pairs D17S1825/D17S1874, D17S1874/D17S807, D17S807/D17S1813, D17S1813/ATA43A10 and ATA43A10/D17S789, and monitored those with a frequency >5% for transmission to MS patients. Typically there were four to six two-marker haplotypes with the minimal 5% frequency seen with each marker pair. We found three two-marker haplotypes (D17S1825/D17S1874, D17S1813/ATA43A109 and ATA43A10/D17S789) showing weak evidence for transmission distortion with P-values 0.029, 0.018 and 0.016, respectively, by the 
2 test (not corrected for multiple testing) in a subset of families originating from the high-risk region of Southern Ostrobothnia (Fig. 1: sets 1a+2a+3a). However, none of the two-marker haplotypes showed significant transmission disequilibrium when tested in the whole sample set (Fig. 1: sets 1+2+3). We also monitored all three-marker haplotypes, which were observed in more than five families, for transmission disequilibrium. A total of 30 three-marker haplotypes were observed in more than five families, of which seven were differentially transmitted to the MS patients of families originating from Southern Ostrobothnia (Table 3). Interestingly, one of the seven three-marker haplotypes (D17S1813, ATA43A10, D17S789) showed some evidence for transmission disequilibrium (P=0.01, not corrected for multiple testing) also in the whole sample set (sets 1+2+3).
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Association analysis
Transmission/disequilibrium test (TDT) and haplotype relative risk (HRR) analysis (31) were performed for 10 markers within and flanking the critical region restricted by the haplotype sharing (D17S1825, D17S1792, D17S1882, D17S1874, D17S1816, D17S807, D17S1813, ATA108A5, ATA43A10 and D17S789) in 22 multiplex and 41 single affected families originating from the high-risk region of Southern Ostrobothnia (sets 1a+2a). Two of the markers, (D17S1825 and D17S1813) provided nominal evidence for association in the HRR analysis (P=0.027 and 0.032, respectively). To verify this finding, we genotyped the markers D17S1825 and D17S1813 in the 250 new trios (set 3) and carried out the HRR and TDT analyses. The weak association seen with the marker D17S1825 in the original data set (set 1a+2a) was replicated in the subset of the new families originating from the high-risk region (set 3a), but could not be replicated in the whole data set 3 (Table 4). Pooling the data of all families originating from the high-risk region (sets 1a+2a+3a) resulted in a somewhat more significant P-value of 0.001 in the HRR analysis (Table 4). The nominal evidence for association seen with the marker D17S1813 in the first set of families could not be replicated in the whole set 3 or a subset set 3a (Table 4).
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Linkage analyses using linkage disequilibrium
We also performed a test of linkage allowing for the presence of linkage disequilibrium (LD) using the PSEUDOMARKER program (32) with the six markers located within and flanking the shared haplotype region, in families originating from the high-risk subisolate (sets 1a+2a+3a) and in families from the other parts of Finland (sets 1b+2b+3b). The LOD scores for linkage without LD for all markers were positive in both sample sets. In a joint test for linkage and LD, the marker D17S1825 provided a corrected P-value of 0.031, suggesting association with MS in families originating from the high-risk region of Southern Ostrobothnia (n=155), whereas the marker D17S807 located 2 cM distant provided similar evidence for association (corrected P=0.022) in families from the other parts of Finland (n=290).
Multipoint linkage analysis
Multipoint analyses were calculated with the Genehunter (33) and SIMWALK 2.40 (30) programs using genotypes of the 22 ordered markers in 22 Southern Ostrobothnia MS families (set 1a). The Genehunter LOD peaked at 3.23 (allowing locus heterogeneity) between the markers D17S1882 and ATA43A10, and the non-parametric (NPL) score peaked at 5.98 (P=0.00019) in an 4 cM interval containing the markers D17S1882, D17S1874, D17S1816, D17S807, D17S1813 and ATA108A5 (Fig. 4). This is in agreement with the critical region predicted by the shared haplotypes in families.
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To be able to use all the genotype information of the large families and to avoid family-size restrictions with the Genehunter program, SIMWALK 2.40 was used. The location score analysis was performed in 22 large families originating from the high-risk region (set 1a) with the affected only strategy and a penetrance of 0.05 allowing no phenocopies. The results indicated approximately the same region as identified using the Genehunter program, between D17S1882 and ATA43A10, peaking at the marker D17S1813 with the LOD score of 2.24 (not shown).
SIMWALK 2.40 clustering analysis was used to review the degree of clustering of the founder alleles among the affecteds (30). Among four SIMWALK statistics, statistic B is the most powerful for detecting linkage to a dominant trait. It provided further evidence for linkage to the region restricted by the marker haplotype, with best evidence for an 2 cM interval containing the markers D17S1882, D17S1874, D17S1816, D17S807 and D17S1813 with an empirical P-value of 0.001 in a subset of 22 families from the high-risk region.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONRESULTSDISCUSSIONMATERIALS AND METHODSREFERENCES |
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The long arm of chromosome 17 has been suggested to be involved in the genetic predisposition to MS disease in multiple studies. Genome-wide scans in British and Finnish families have previously produced some evidence for linkage to this region (14,15). Further, suggestive evidence for linkage as well as significant transmission disequilibrium in the TDT test were observed with one marker mapping to this region in a recent study in Canadian sibling pairs (24). Given the complex nature and the existing evidence for genetic heterogeneity of MS, genetic predisposition is most likely due to interactions between several genes and influenced by so-far unknown non-genetic factors. In order to minimize genetic heterogeneity, we have targeted our fine-mapping effort to relatively rare MS families with multiple affected individuals and a most probable enrichment of some genes in the background of the disease in the regional sub-isolate of Finland.
By analyzing the marker haplotypes spanning a 23 cM interval on chromosome 17q22–q24 in 22 multiplex MS families from the high-risk region, we were not able to find a single shared haplotype in putative disease alleles. This might be explained by the fact that the high-risk geographical region is part of the early-settlement region, where the population is close to 2000 years old (18,34). Thus, although potentially exposing shared ancestral MS alleles, the old age of putative founder mutation(s) would result in short LD intervals (19,34). However, we identified a 4 cM DNA region, shared by the affected individuals of each family, in 77% of families originating from the subisolate, the same region being also shared by the affected individuals in 83% of the multiplex families originating from the other parts of Finland (n=6). Additional support for this region came from multipoint analyses yielding an NPL score of 5.98 over this 4 cM region, and the SIMWALK 2.40 clustering analysis showed the best evidence for linkage to a 2 cM region within this interval. Further, a three-marker haplotype constructed with markers within (D17S1813) and flanking (ATA43A10 and D17S789) this region showed some evidence for transmission disequilibrium in the whole study sample, representing a nationwide collection of MS families and trios. Interestingly, D17S789 was also implicated for association with MS in a recent Canadian study of 333 sibling pairs (24). This particular marker alone showed no evidence for association with MS in this study, while D17S1825, located 4 cM distant, revealed nominal evidence for association both in the original analysis of 63 MS families from the high-risk region and in the set of additional MS trios from the high-risk region. HRR analysis in the combined study sample from the high-risk region provided stronger evidence for association. The association in MS alleles of a regional subisolate and the lack of association in study samples from other parts of Finland is not surprising. Expanding the study sample to the whole population certainly increases both genetic and environmental heterogeneity.
Regional candidate genes
There are at least 11 full-length mRNAs with known function and 75 expressed sequence tag (EST) contigs and predicted transcripts within the critical 2.5 Mb region. Of the interesting functional or positional candidate genes, AXIN2, APOH, PRKCA, CACNG1, CACNG4, CACNG5, RCH1, BPTF, FALZ, SLC16A6 and RDGBB are in the region suggested by the shared haplotype, and biologically highly relevant genes such as ICAM2 and PECAM1 map in the immediate vicinity. Previous studies have reported an association for a promoter polymorphism of the MPO gene with MS in two population samples (35,36). Further, knockout mice lacking the MPO gene were shown to be more prone to Eae, the murine MS model, than their healthy littermates (37). However, we were not able to see association with MS in our study sample using a marker (D17S1290) located <100 kb proximal to MPO, and this gene mapped outside the critical region restricted by shared haplotypes. Also, studies in the US, Scandinavian and Sardinian populations have failed to detect any association to MS with the MPO gene, or the two other genes, PECAM1 and PRKAR1A, that are also located within this chromosomal region (38,39). Further, neither ICAM2 nor PECAM1 provided evidence for association with MS in our preliminary analysis using single-nucleotide polymorphisms (SNPs) in the promoter, coding and non-coding regions of these genes (D. Chen et al., unpublished results). However, both are biologically relevant genes encoding crucial components of cell-mediated immunity, and, further, ICAM2 was one of the 62 genes observed to be differentially expressed in a study comparing gene expression profiles of acute MS lesions and normal white matter (40). Although the study design may favor observations of expression differences seen as an end result of the immunological reaction rather than differences in causative genes, further studies with ICAM-2 are still justified. Genes coding ion channels, CACNG1, -4 and -5, also represent interesting candidate genes taking into account the recent findings of sensory neuron-specific sodium channels (SNS) being abnormally expressed in the brains of mice with Eae and humans with MS (41).
Interestingly, although the mouse Eae locus (27) does not overlap with the human region defined here, the rat chromosome 10 locus (25), which is synthenic to human chromosome 17, shares several genes, including SCN4A, PRKCA and PRKAR1A, with the human locus, making them interesting positional candidates for MS.
To summarize, by using the combined power of linkage, linkage disequilibrium and shared haplotype analyses, successfully utilized in the fine mapping of monogenic diseases, we were able to restrict the MS locus on chromosome 17q from 23 cM to a <4 cM region covering a physical interval of 2.5 Mb. This chromosomal region contains several interesting functional candidates for MS—and those, as well as many of the still uncharacterized transcripts mapping to this interval, are currently being studied in Finnish MS families using the SNPs within these genes. Although lacking definitive evidence for association with MS with any of the markers mapping within this chromosomal region, we define this as one of the primary target regions for the future search for the MS predisposing gene(s) in the Finnish families, and definitely worthwhile of analyses in other populations.
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONRESULTSDISCUSSIONMATERIALS AND METHODSREFERENCES |
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MS pedigrees
The principal study material consisted of 28 multiplex MS families with two to six affected cases per pedigree (set 1 in Fig. 1), and 167 MS patients with their parents and/or unaffected sibs (set 2). Twenty-two of the multiplex families are identical to those previously used and described in our genetic mapping studies 15,20–23), except for one patient previously diagnosed with optic neuritis, who more recently developed clinically definitive MS. Two of the remaining six new multiplex families were originally collected as single affected families, but could be traced to the same pedigrees using genealogical studies and population records. Twenty-two of the multiplex families (set 1a) and 41 of the single affected families (set 2a) originated from Southern Ostrobothnia region in the western part of Finland, while 6 multiplex (set 1b) and 126 trio families (set 2b) originated from other parts of Finland.
In an extension to the principal study sample, we collected 250 new nuclear families, mostly trios (affected family member and her/his parents). Ninety-two of them originate from Southern Ostrobothnia (set 3a), 56 from southern Finland, 87 from eastern Finland and 15 from northern Finland (set 3b).
Diagnosis of MS in affected individuals strictly followed Poser's diagnostic criteria (42). One patient with a diagnosis of optic neuritis is a member of a family with multiple MS cases originating from the high-risk region, and thus, in the present study, was regarded as affected. Three asymptomatic siblings had lesions typical of MS on magnetic resonance imagining (MRI), and their affection status was regarded as unknown in the analysis.
Integrated map
We used multiple approaches to create an integrated map of the 23 cM region on 17q22–q24 potentially containing gene(s) for MS. First, 20 out of 35 markers shown in Whitehead maps (http://www.wi.mit.edu/) to map to the contigs 17.7–17.9 were confirmed to map to YAC/BAC clones by PCR using primer sequences and standard conditions as published for each primer pair. Second, 26 out of 35 markers shown in Figure 1 were used for radiation hybrid mapping analysis using the Stanford G3 and TNG radiation hybrid mapping panels according to the standard protocol (Research Genetics, Huntsville, AL). Third, FISH with 10 clones was used to confirm the clone order predicted by other methods (Fig. 1). Multicolor FISH to normal and mechanically stretched chromosomes was used to determine the precise order of the clones hrpk.146P2, hcit.462L7, hrpk.178C3, hcit.217L10, hrpk.156L14, hrpk.269G24, 120L21, hrpk.346K10, 493C2, hrpk.147L13 and YAC 942G11 (shown in column 7 of Fig. 2) as described previously (43,44).
The minimum markers necessary to confirm our predicted order of markers used for linkage and haplotype analysis are shown in Figure 2 (although >95 sequence tagged sites and 70 clones were used to complete the map). Finally, BLAST searches against the NCBI (http://www.ncbi.nlm.nih.gov/) and Celera (45) (http://www.celera.com) databases were performed for all 37 markers when these sequences became available.
Genotyping
DNA was extracted from EDTA blood according to standard procedures. The markers were selected from the Whitehead database (http://www-genome.wi.mit.edu/). The order of the markers and the distances between them were determined or confirmed in this study. Thirty-one markers were genotyped in data set 1a (22 multiplex families originating from Southern Ostrobothnia) and the part of data set 2 (set 2a) originating from Southern Ostrobothnia. Additionally, the six markers within and flanking the critical region (D17S1825, D17S1874, D17S807, D17S1813, ATA43A10 and D17S789) were also genotyped in the sample set 2b and the whole sample set 3 (D17S1813 only in sample set 3).
For genotyping, PCR reactions were performed with a fluorescently labeled forward primer under standard conditions with a PCR protocol optimized for each primer pair. The labeled PCR products were separated on a LI-COR model 4200 Dual Dye automated DNA sequencing system, and the gels were analyzed using the SAGA Automated Genetic Analysis Software (LI-COR, US). All genotypes were checked for incompatibilities by PedCheck 1.0 (46), and either incompatibilities were resolved unambiguously or the families with errors were discarded from analysis for the actual marker. The multipoint mistyping analysis option of SIMWALK 2, version 2.82 (47) was used to identify possible, non-Mendelian genotyping errors in the markers selected for haplotype and multipoint analyses.
Haplotype construction
First, we constructed marker haplotypes in 21 large pedigrees originating from Southern Ostrobothnia (set 1a) using 23 ordered markers in chromosome 17 with SIMWALK 2.40 (30). All the haplotypes were also checked by eye, by two researchers separately. In two large pedigrees (pedigrees 2 and 5), we observed two haplotypes, each shared by the affected individuals of one-half of the pedigree (2+4 affected cases in pedigree 2, and 3+1 affected cases in pedigree 5), originating most probably from persons married into the family rather than from a common ancestor. These pedigrees were divided into two families (2A, 2B, 5A and 5B, respectively) for multipoint linkage studies to minimize the complexity.
Second, haplotypes were constructed with six markers (D17S1825, D17S1874, D17S807, D17S1813, ATA43A10 and D17S789) in six additional multiplex families (set 1b) and in 167 (set 2) and 250 (set 3) single affected families. Two transmitted and two non-transmitted haplotypes were randomly selected for each large pedigree for evaluating the transmission distortion. The differences in haplotype frequency distribution between transmitted and non-transmitted haplotypes were tested by the 2 test and the uncorrected P-values are shown.
Linkage analysis
To incorporate complete pedigree information in the statistical analysis, we used two-point linkage analysis for the fine mapping with the multiplex MS pedigrees originating from Southern Ostrobothnia. Two-point linkage analyses were performed using the MLINK program of the LINKAGE package, FASTLINK version 2.2 (28,29).
Multipoint, parametric and non-parametric linkage analyses were performed using the Genehunter computer package (33). To use all the information from the large families and avoid family-size restrictions, the SIMWALK 2.40 program, version 2.6 was used to calculate location score and clustering analysis (30). The multipoint analyses were performed on 22 multiplex pedigrees originating from Southern Ostrobothnia. The parameters used in the parametric linkage analyses were dominant model and penetrances for DD and Dd individuals (D= disease) f=0.05, and for dd individuals f=0.00. A gene frequency of 0.01 was used, as described previously (15).
The HRR and TDT approaches were used to monitor for association (31). For joint analysis of large pedigrees and single affected families, a model-free LOD score analysis in which haplotype frequencies were treated as a nuisance parameter was performed with PSEUDOMARKER (32) using the modified version of ILINK of the FASTLINK4.1P package (28,29,48; A. Schäffer, personal communication). In the analysis, one mode of inheritance was considered in which affected relatives were expected to share the transmission of one copy of the disease allele. The disease locus was modeled as a diallelic locus, and for trio families one parent was arbitrarily assigned disease locus genotype 1/1 and the other 1/2, with affected children having genotype 1/2. Thus, the analysis makes use of all the data jointly to extract the maximum linkage and association information possible. A simple two-point analysis, in which haplotype frequencies were estimated separately as nuisance parameters under linkage and no linkage, was then carried out for each marker versus the disease trait. LOD scores were computed as described previously (31,32).
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ACKNOWLEDGEMENTS |
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We thank Tero Hiekkalinna and Perttu Haimi for their help in biocomputing. Drs Joseph Terwilliger, Janet Sinsheimer, Rita Cantor and Kenneth Lange are appreciated for their valuable comments concerning statistical analyses. We also wish to thank the participating Finnish MS families. This work was supported financially by the Center of Excellence for Disease Genetics of the Academy of Finland and the Multiple Sclerosis Foundation of the USA (to L.P.), and by grants from the Cultural Foundation of Finland, the Multiple Sclerosis Foundation of Finland and the Science and Research Foundation of Farmos (to J.S. and S.F.), from the Finnish Academy, Maire Taponen Foundation and the Paulo Foundation (to S.F.), and from the Sigrid Jusélius Foundation, Helsinki University Central Hospital (to P.T.).
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FOOTNOTES |
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* To whom correspondence should be addressed at: Department of Human Genetics, UCLA School of Medicine, Gonda Center, 695 Charles E. Young Drive South, Box 708822, Los Angeles, CA 90095-7088, USA. Tel: +1 3107945631; Fax: +1 3107945446; Email: lpeltonen{at}mednet.ucla.edu
The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors.
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REFERENCES |
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