A recent high-density linkage screen confirmed that the HLA complex contains the strongest genetic factor for the risk of multiple sclerosis (MS). In parallel, a linkage disequilibrium analysis using 650 single nucleotide polymorphisms (SNP) markers of the HLA complex mapped the entire genetic effect to the HLA-DR-DQ subregion, reflected by the well-established risk haplotype HLA-DRB1*15,DQB1*06. Contrary to this, in a cohort of 1,084 MS patients and 1,347 controls, we show that the HLA-A gene confers an HLA-DRB1 independent influence on the risk of MS (P = 8.4×10−10). This supports the opposing view, that genes in the HLA class I region indeed exert an additional influence on the risk of MS, and confirms that the class I allele HLA-A*02 is negatively associated with the risk of MS (OR = 0.63, P = 7×10−12) not explained by linkage disequilibrium with class II. The combination of HLA-A and HLA-DRB1 alleles, as represented by HLA-A*02 and HLA-DRB1*15, was found to influence the risk of MS 23-fold. These findings imply complex autoimmune mechanisms involving both the regulatory and the effector arms of the immune system in the triggering of MS.

Multiple sclerosis (MS) is a T-cell-mediated disease of the central nervous system, characterized by damage to myelin and axons, resulting in progressive neurological disability. Genes may influence susceptibility to MS, but results of association studies are inconsistent, aside from the identification of HLA class II haplotypes. Whole-genome linkage screens in MS have both confirmed the importance of the HLA region and uncovered non-HLA loci that may harbor susceptibility genes. In this twostage analysis, we determined genotypes, in up to 672 MS patients and 672 controls, for 123 single-nucleotide polymorphisms (SNPs) in 66 genes. Genes were chosen based on their chromosomal positions or biological functions. In stage one, 22 genes contained at least one SNP for which the carriage rate for one allele differed significantly (Po0.08) between patients and controls. After additional genotyping in stage two, two genes-each containing at least three significantly (Po0.05) associated SNPs-conferred susceptibility to MS: LAG3 on chromosome 12p13, and IL7R on 5p13. LAG3 inhibits activated T cells, while IL7R is necessary for the maturation of T and B cells. These results imply that germline allelic variation in genes involved in immune homeostasis-and, by extension, derangement of immune homeostasis-influence the risk of MS.

The human leucocyte antigen (HLA) class II haplotype DRB1*15-DQB1*06 (DR15-DQ6) is associated with susceptibility to multiple sclerosis (MS), and HLA class I associations in MS have also been reported. However, the influence of HLA class I and II alleles on clinical phenotypes in MS has not yet been completely studied. This study aimed at evaluating the impact of HLA-A and -DRB1 alleles on clinical variables in Scandinavian MS patients. The correlation between HLA-A or -DRB1 alleles and age at onset, disease course and Multiple Sclerosis Severity Score (MSSS) were studied in 1457 Norwegian and Swedish MS patients by regression analyses and Kruskal-Wallis rank sum test. Presence of HLA-DRB1*15 was correlated with younger age at onset of disease (corrected P = 0.009). No correlation was found between HLA-A and the variables studied. This study analysed the effect of HLA-A on clinical variables in a large Scandinavian sample set, but could not identify any significant contribution from HLA-A on the clinical phenotype in MS. However, associations between HLA-DRB1*15 and age at onset of MS were reproduced in this extended Scandinavian MS cohort.

We present a score for testing association in the presence of linkage for binary traits. The score is robust to varying degrees of linkage, and it is valid under any ascertainment scheme based on trait values as well as under population stratification. The score test is derived from a mixed effects model where population level association is modeled using a fixed effect and where correlation among related individuals is allowed for by using log-gamma random effects. The score, as presented in this paper, does not assume full information about the inheritance pattern in families or parental genotypes. We compare the score to the semi-parametric family-based association test (FBAT), which has won ground because of its flexible and simple form. We show that a random effects formulation of co-inheritance can improve the power substantially. We apply the method to data from the Collaborative Study on the Genetics of Alcoholism. We compare our findings to previously published results.

Introduction The c.1-34T>C 5' promoter region polymorphism in cytochrome P450c17 (CYP17), a key enzyme in the biosynthesis of estrogen, has been associated with breast cancer risk, but most previous studies have been relatively small.