Coronary artery disease (CAD) is the commonest cause of death. Here, we report an association analysis in 63,746 CAD cases and 130,681 controls identifying 15 loci reaching genome-wide significance, taking the number of susceptibility loci for CAD to 46, and a further 104 independent variants (r2 < 0.2) strongly associated with CAD at a 5% false discovery rate (FDR). Together, these variants explain approximately 10.6% of CAD heritability. Of the 46 genome-wide significant lead SNPs, 12 show a significant association with a lipid trait, and 5 show a significant association with blood pressure, but none is significantly associated with diabetes. Network analysis with 233 candidate genes (loci at 10% FDR) generated 5 interaction networks comprising 85% of these putative genes involved in CAD. The four most significant pathways mapping to these networks are linked to lipid metabolism and inflammation, underscoring the causal role of these activities in the genetic etiology of CAD. Our study provides insights into the genetic basis of CAD and identifies key biological pathways.

Despite improvements in the prognosis of childhood acute lymphoblastic leukemia (ALL), subgroups of patients would benefit from alternative treatment approaches. Our aim was to identify genes with DNA methylation profiles that could identify such groups. We determined the methylation levels of 1320 CpG sites in regulatory regions of 416 genes in cells from 401 children diagnosed with ALL. Hierarchical clustering of 300 CpG sites distinguished between T-lineage ALL and B-cell precursor (BCP) ALL and between the main cytogenetic subtypes of BCP ALL. It also stratified patients with high hyperdiploidy and t(12;21) ALL into 2 subgroups with different probability of relapse. By using supervised learning, we constructed multivariate classifiers by external cross-validation procedures. We identified 40 genes that consistently contributed to accurate discrimination between the main subtypes of BCP ALL and gene sets that discriminated between subtypes of ALL and between ALL and controls in pairwise classification analyses. We also identified 20 individual genes with DNA methylation levels that predicted relapse of leukemia. Thus, methylation analysis should be explored as a method to improve stratification of ALL patients. The genes highlighted in our study are not enriched to specific pathways, but the gene expression levels are inversely correlated to the methylation levels. (Blood. 2010;115:1214-1225)

Background:IRF5 is a transcription factor involved both in the type I interferon and the toll-like receptor signalling pathways. Previously, IRF5 has been found to be associated with systemic lupus erythematosus, rheumatoid arthritis and inflammatory bowel diseases. Here we investigated whether polymorphisms in the IRF5 gene would be associated with yet another disease with features of autoimmunity, multiple sclerosis (MS).Methods:We genotyped nine single nucleotide polymorphisms and one insertion-deletion polymorphism in the IRF5 gene in a collection of 2337 patients with MS and 2813 controls from three populations: two case–control cohorts from Spain and Sweden, and a set of MS trio families from Finland.Results:Two single nucleotide polymorphism (SNPs) (rs4728142, rs3807306), and a 5 bp insertion-deletion polymorphism located in the promoter and first intron of the IRF5 gene, showed association signals with values of p<0.001 when the data from all cohorts were combined. The predisposing alleles were present on the same common haplotype in all populations. Using electrophoretic mobility shift assays we observed allele specific differences in protein binding for the SNP rs4728142 and the 5 bp indel, and by a proximity ligation assay we demonstrated increased binding of the transcription factor SP1 to the risk allele of the 5 bp indel.Conclusion:These findings add IRF5 to the short list of genes shown to be associated with MS in more than one population. Our study adds to the evidence that there might be genes or pathways that are common in multiple autoimmune diseases, and that the type I interferon system is likely to be involved in the development of these diseases.

We performed a candidate gene association study in 540 patients with primary Sjö gren's Syndrome (SS) from Sweden (n ¼ 344) and Norway (n ¼ 196) and 532 controls (n ¼ 319 Swedish, n ¼ 213 Norwegian). A total of 1139 single-nucleotide polymorphisms (SNPs) in 84 genes were analyzed. In the meta-analysis of the Swedish and Norwegian cohorts, we found high signals for association between primary SS and SNPs in three gene loci, not previously associated with primary SS. These are the early B-cell factor 1 (EBF1) gene, P ¼ 9.9 Â 10 À5 , OR 1.68, the family with sequence similarity 167 member A-B-lymphoid tyrosine kinase (FAM167A-BLK) locus, P ¼ 4.7 Â 10 À4 , OR 1.37 and the tumor necrosis factor superfamily (TNFSF4 ¼ Ox40L) gene, P ¼ 7.4 Â 10 À4 , OR 1.34. We also confirmed the association between primary SS and the IRF5/TNPO3 locus and the STAT4 gene. We found no association between the SNPs in these five genes and the presence of anti-SSA/anti-SSB antibodies. EBF1, BLK and TNFSF4 are all involved in B-cell differentiation and activation, and we conclude that polymorphisms in several susceptibility genes in the immune system contribute to the pathogenesis of primary SS.

To identify genes that are regulated by cis-acting functional elements in acute lymphoblastic leukemia (ALL) we determined the allele-specific expression (ASE) levels of 2529 genes by genotyping a genome-wide panel of single nucleotide polymorphisms in RNA and DNA from bone marrow and blood samples of 197 children with ALL. Using a reproducible, quantitative genotyping method and stringent criteria for scoring ASE, we found that 16% of the analyzed genes display ASE in multiple ALL cell samples. For most of the genes, the level of ASE varied largely between the samples, from 1.4-fold overexpression of one allele to apparent monoallelic expression. For genes exhibiting ASE, 55% displayed bidirectional ASE in which overexpression of either of the two SNP alleles occurred. For bidirectional ASE we also observed overall higher levels of ASE and correlation with the methylation level of these sites. Our results demonstrate that CpG site methylation is one of the factors that regulates gene expression in ALL cells.

A large number of genome-wide association studies have been performed during the past five years to identify associations between SNPs and human complex diseases and traits. The assignment of a functional role for the identified disease-associated SNP is not straight-forward. Genome-wide expression quantitative trait locus (eQTL) analysis is frequently used as the initial step to define a function while allele-specific gene expression (ASE) analysis has not yet gained a wide-spread use in disease mapping studies. We compared the power to identify cis-acting regulatory SNPs (cis-rSNPs) by genome-wide allele-specific gene expression (ASE) analysis with that of traditional expression quantitative trait locus (eQTL) mapping. Our study included 395 healthy blood donors for whom global gene expression profiles in circulating monocytes were determined by Illumina BeadArrays. ASE was assessed in a subset of these monocytes from 188 donors by quantitative genotyping of mRNA using a genome-wide panel of SNP markers. The performance of the two methods for detecting cis-rSNPs was evaluated by comparing associations between SNP genotypes and gene expression levels in sample sets of varying size. We found that up to 8-fold more samples are required for eQTL mapping to reach the same statistical power as that obtained by ASE analysis for the same rSNPs. The performance of ASE is insensitive to SNPs with low minor allele frequencies and detects a larger number of significantly associated rSNPs using the same sample size as eQTL mapping. An unequivocal conclusion from our comparison is that ASE analysis is more sensitive for detecting cis-rSNPs than standard eQTL mapping. Our study shows the potential of ASE mapping in tissue samples and primary cells which are difficult to obtain in large numbers.

To characterize the mutational patterns of acute lymphoblastic leukemia (ALL) we performed deep next generation sequencing of 872 cancer genes in 172 diagnostic and 24 relapse samples from 172 pediatric ALL patients. We found an overall greater mutational burden and more driver mutations in T-cell ALL (T-ALL) patients compared to B-cell precursor ALL (BCP-ALL) patients. In addition, the majority of the mutations in T-ALL had occurred in the original leukemic clone, while most of the mutations in BCP-ALL were subclonal. BCP-ALL patients carrying any of the recurrent translocations ETV6-RUNX1, BCR-ABL or TCF3-PBX1 harbored few mutations in driver genes compared to other BCP-ALL patients. Specifically in BCP-ALL, we identified ATRX as a novel putative driver gene and uncovered an association between somatic mutations in the Notch signaling pathway at ALL diagnosis and increased risk of relapse. Furthermore, we identified EP300, ARID1A and SH2B3 as relapse-associated genes. The genes highlighted in our study were frequently involved in epigenetic regulation, associated with germline susceptibility to ALL, and present in minor subclones at diagnosis that became dominant at relapse. We observed a high degree of clonal heterogeneity and evolution between diagnosis and relapse in both BCP-ALL and T-ALL, which could have implications for the treatment efficiency.

To detect genes with CpG sites that display methylation patterns that are characteristic of acute lymphoblastic leukemia (ALL) cells, we compared the methylation patterns of cells taken at diagnosis from 20 patients with pediatric ALL to the methylation patterns in mononuclear cells from bone marrow of the same patients during remission and in non-leukemic control cells from bone marrow or blood. Using a custom-designed assay, we measured the methylation levels of 1,320 CpG sites in regulatory regions of 413 genes that were analyzed because they display allele-specific gene expression (ASE) in ALL cells. The rationale for our selection of CpG sites was that ASE could be the result of allele-specific methylation in the promoter regions of the genes. We found that the ALL cells had methylation profiles that allowed distinction between ALL cells and control cells. Using stringent criteria for calling differential methylation, we identified 28 CpG sites in 24 genes with recurrent differences in their methylation levels between ALL cells and control cells. Twenty of the differentially methylated genes were hypermethylated in the ALL cells, and as many as nine of them (AMICA1, CPNE7, CR1, DBC1, EYA4, LGALS8, RYR3, UQCRFS1, WDR35) have functions in cell signaling and/or apoptosis. The methylation levels of a subset of the genes were consistent with an inverse relationship with the mRNA expression levels in a large number of ALL cells from published data sets, supporting a potential biological effect of the methylation signatures and their application for diagnostic purposes.