Association of the HLA region with multiple sclerosis as confirmed by a genome screen using >10,000 SNPs on DNA chips.

Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system, with a complex genetic background. Here, we present a genome screen for association in small scale, employing 11,555 single nucleotide polymorphisms (SNPs) on DNA chips for genotyping 100 MS patients stratified for HLA-DR2+ and 100 controls. More than 500 SNPs revealed significant differences between cases and controls before Bonferroni correction. A fraction of these SNPs was reanalysed in two additional cohorts of patients and controls, using high-throughput genotyping methods. A marker on chromosome 6p21.32 (rs2395182) yielded the highest significance level, validating the established HLA-DR association.

Investigation of the HLA-DRB1 locus in alopecia areata.

To further evaluate the nature of the HLA association with alopecia areata (AA), we investigated the HLA-DRB1 locus in 161 AA patients and 165 matched controls from Belgium and Germany. HLA-DRB1 typing was performed using a recently established method that employs a combination of PCR-SSP (sequence specific priming) and Pyrosequencing(TM) technology. No significant differences were observed for HLA allele groups DRB1 *01, *07, *08, *09, *10, *11, *13, *14, *15, and *16. HLA-DRB1*03 was found to confer a protective effect (7.5% versus 13.6%, p = 0.011). Additional genotyping at the allelic level revealed a significant difference in HLA-DRB1*0301 between patients and controls (6.8% versus 11.2%, p = 0.048). The DRB1*04 allele group was confirmed as a risk factor for the development of AA (20.8% versus 13.3%, p = 0.012), with the allele DRB1*0401 accounting for the greatest proportion of the effect (13.4% versus 7.3%, p = 0.014). Results obtained after subgrouping of the patients according to age at onset, severity and family history of the disease suggests that the genetic effects of the HLA system are strongest in familial cases of the disease.

SNP-based analysis of genetic substructure in the German population.

OBJECTIVE: To evaluate the relevance and necessity to account for the effects of population substructure on association studies under a case-control design in central Europe, we analysed three samples drawn from different geographic areas of Germany. Two of the three samples, POPGEN (n = 720) and SHIP (n = 709), are from north and north-east Germany, respectively, and one sample, KORA (n = 730), is from southern Germany. METHODS: Population genetic differentiation was measured by classical F-statistics for different marker sets, either consisting of genome-wide selected coding SNPs located in functional genes, or consisting of selectively neutral SNPs from 'genomic deserts'. Quantitative estimates of the degree of stratification were performed comparing the genomic control approach [Devlin B, Roeder K: Biometrics 1999;55:997-1004], structured association [Pritchard JK, Stephens M, Donnelly P: Genetics 2000;155:945-959] and sophisticated methods like random forests [Breiman L: Machine Learning 2001;45:5-32]. RESULTS: F-statistics showed that there exists a low genetic differentiation between the samples along a north-south gradient within Germany (F(ST)(KORA/POPGEN): 1.7 . 10(-4); F(ST)(KORA/SHIP): 5.4 . 10(-4); F(ST)(POPGEN/SHIP): -1.3 . 10(-5)). CONCLUSION: Although the F(ST )-values are very small, indicating a minor degree of population structure, and are too low to be detectable from methods without using prior information of subpopulation membership, such as STRUCTURE [Pritchard JK, Stephens M, Donnelly P: Genetics 2000;155:945-959], they may be a possible source for confounding due to population stratification.