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The recent development of whole genome association studies has lead to the robust identification of several loci involved in different common human diseases. Interestingly, some of the strongest signals of association observed in these studies arise from non-coding regions located in very large introns or far away from any annotated genes, raising the possibility that these regions are involved in the etiology of the disease through some unidentified regulatory mechanisms. These findings highlight the importance of better understanding the mechanisms leading to inter-individual differences in gene expression in humans. Most of the existing approaches developed to identify common regulatory polymorphisms are based on linkage/association mapping of gene expression to genotypes. However, these methods have some limitations, notably their cost and the requirement of extensive genotyping information from all the individuals studied which limits their applications to a specific cohort or tissue. Here we describe a robust and high-throughput method to directly measure differences in allelic expression for a large number of genes using the Illumina Allele-Specific Expression BeadArray platform and quantitative sequencing of RT-PCR products. We show that this approach allows reliable identification of differences in the relative expression of the two alleles larger than 1.5-fold (i.e., deviations of the allelic ratio larger than 60:40) and offers several advantages over the mapping of total gene expression, particularly for studying humans or outbred populations. Our analysis of more than 80 individuals for 2,968 SNPs located in 1,380 genes confirms that differential allelic expression is a widespread phenomenon affecting the expression of 20% of human genes and shows that our method successfully captures expression differences resulting from both genetic and epigenetic cis-acting mechanisms.

Adaptor protein (AP) complexes regulate clathrin-coated vesicle assembly, protein cargo sorting, and vesicular trafficking between organelles in eukaryotic cells. Because disruption of the various subunits of the AP complexes is embryonic lethal in the majority of cases, characterization of their function in vivo is still lacking. Here, we describe the first mutation in the human AP1S1 gene, encoding the small subunit sigma1A of the AP-1 complex. This founder splice mutation, which leads to a premature stop codon, was found in four families with a unique syndrome characterized by mental retardation, enteropathy, deafness, peripheral neuropathy, ichthyosis, and keratodermia (MEDNIK). To validate the pathogenic effect of the mutation, we knocked down Ap1s1 expression in zebrafish using selective antisens morpholino oligonucleotides (AMO). The knockdown phenotype consisted of perturbation in skin formation, reduced pigmentation, and severe motility deficits due to impaired neural network development. Both neural and skin defects were rescued by co-injection of AMO with wild-type (WT) human AP1S1 mRNA, but not by co-injecting the truncated form of AP1S1, consistent with a loss-of-function effect of this mutation. Together, these results confirm AP1S1 as the gene responsible for MEDNIK syndrome and demonstrate a critical role of AP1S1 in development of the skin and spinal cord.

Background Genetic variants at the vitamin D receptor (VDR) locus are associated with asthma and atopy. We hypothesized that polymorphisms in other genes of the vitamin D pathway are associated with asthma or atopy. Methods Eleven candidate genes were chosen for this study, five of which code for proteins in the vitamin D metabolism pathway ( CYP27A1 , CYP27B1 , CYP2R1 , CYP24A1 , GC ) and six that are known to be transcriptionally regulated by vitamin D ( IL10 , IL1RL1 , CD28 , CD86 , IL8 , SKIIP ). For each gene, we selected a maximally informative set of common SNPs (tagSNPs) using the European-derived (CEU) HapMap dataset. A total of 87 SNPs were genotyped in a French-Canadian family sample ascertained through asthmatic probands (388 nuclear families, 1064 individuals) and evaluated using the Family Based Association Test (FBAT) program. We then sought to replicate the positive findings in four independent samples: two from Western Canada, one from Australia and one from the USA (CAMP). Results A number of SNPs in the IL10 , CYP24A1 , CYP2R1 , IL1RL1 and CD86 genes were modestly associated with asthma and atopy (p < 0.05). Two-gene models testing for both main effects and the interaction were then performed using conditional logistic regression. Two-gene models implicating functional variants in the IL10 and VDR genes as well as in the IL10 and IL1RL1 genes were associated with asthma (p < 0.0002). In the replicate samples, SNPs in the IL10 and CYP24A1 genes were again modestly associated with asthma and atopy (p < 0.05). However, the SNPs or the orientation of the risk alleles were different between populations. A two-gene model involving IL10 and VDR was replicated in CAMP, but not in the other populations. Conclusion A number of genes involved in the vitamin D pathway demonstrate modest levels of association with asthma and atopy. Multilocus models testing genes in the same pathway are potentially more effective to evaluate the risk of asthma, but the effects are not uniform across populations.

A survey of epigenetic associations between serum immunoglobulin E concentrations indicating allergy and methylation at CpG islands in families and a population sample has revealed associations at 36 loci that harbour genes encoding proteins including eosinophil products and phospholipid inflammatory mediators. IgE blocker targets identified Drugs that block immunoglobulin E (IgE) are widely used to treat asthma, hay fever and allergic asthma, but genetic association studies have failed to identify the pathways underlying the pathways that regulate IgE's role in mediating the allergic state. Using DNA from peripheral blood leukocytes, William Cookson and colleagues surveyed families for epigenetic associations between serum IgE concentrations and methylation at CpG islands genome-wide. They identified associations between IgE and low methylation at 36 loci that harbour genes encoding proteins including eosinophil products and phospholipid inflammatory mediators. The three most-associated loci accounted for 13% of IgE variation in the primary subject panel. The study identifies novel therapeutic targets and biomarkers for patient stratification for allergic diseases. Immunoglobulin E (IgE) is a central mediator of allergic (atopic) inflammation. Therapies directed against IgE can alleviate hay fever 1 and allergic asthma 1 , 2 . Genetic association studies have not yet identified novel therapeutic targets or pathways underlying IgE regulation 3 , 4 , 5 , 6 . We therefore surveyed epigenetic associations between serum IgE concentrations and methylation at loci concentrated in CpG islands genome wide in 95 nuclear pedigrees, using DNA from peripheral blood leukocytes. We validated positive results in additional families and in subjects from the general population. Here we show replicated associations—with a meta-analysis false discovery rate less than 10 −4 —between IgE and low methylation at 36 loci. Genes annotated to these loci encode known eosinophil products, and also implicate phospholipid inflammatory mediators, specific transcription factors and mitochondrial proteins. We confirmed that methylation at these loci differed significantly in isolated eosinophils from subjects with and without asthma and high IgE levels. The top three loci accounted for 13% of IgE variation in the primary subject panel, explaining the tenfold higher variance found compared with that derived from large single-nucleotide polymorphism genome-wide association studies 3 , 4 . This study identifies novel therapeutic targets and biomarkers for patient stratification for allergic diseases.

Type 2 diabetes mellitus results from the interaction of environmental factors with a combination of genetic variants, most of which were hitherto unknown. A systematic search for these variants was recently made possible by the development of high-density arrays that permit the genotyping of hundreds of thousands of polymorphisms. We tested 392,935 single-nucleotide polymorphisms in a French case–control cohort. Markers with the most significant difference in genotype frequencies between cases of type 2 diabetes and controls were fast-tracked for testing in a second cohort. This identified four loci containing variants that confer type 2 diabetes risk, in addition to confirming the known association with the TCF7L2 gene. These loci include a non-synonymous polymorphism in the zinc transporter SLC30A8, which is expressed exclusively in insulin-producing β-cells, and two linkage disequilibrium blocks that contain genes potentially involved in β-cell development or function ( IDE–KIF11–HHEX and EXT2–ALX4 ). These associations explain a substantial portion of disease risk and constitute proof of principle for the genome-wide approach to the elucidation of complex genetic traits. Diabetes in the genes Overeating and physical inactivity are major causes of type 2 diabetes mellitus, but they affect only genetically susceptible individuals and the genetic basis of the disease is notoriously complex. Recent research has suggested that specific genes may be associated with the risk of developing the disease, however. Now a genome-wide search using high-density genotyping arrays has identified four previously unknown genes as diabetes risk factors, and confirmed a known association with the TCF7L2 gene. Together these five genes may contribute a sizeable fraction of the disease risk in type 2 diabetes, and analysis of their function should clarify the pathogenesis of diabetes and point to new drug targets. In addition, individuals shown to have these mutations could minimize their risk by adjusting diet. A survey of the entire human genome has found that five genetic loci contribute a large fraction of disease risk in type 2 diabetes.

We have performed a genome-wide analysis of common genetic variation controlling differential expression of transcript isoforms in the CEU HapMap population using a comprehensive exon tiling microarray covering 17,897 genes. We detected 324 genes with significant associations between flanking SNPs and transcript levels. Of these, 39% reflected changes in whole gene expression and 55% reflected transcript isoform changes such as splicing variants (exon skipping, alternative splice site use, intron retention), differential 5′ UTR (initiation of transcription) use, and differential 3′ UTR (alternative polyadenylation) use. These results demonstrate that the regulatory effects of genetic variation in a normal human population are far more complex than previously observed. This extra layer of molecular diversity may account for natural phenotypic variation and disease susceptibility.

Alexandra-Chloé Villani and colleagues have identified SNPs located on chromosome 1q44 downstream of the NLRP3 gene that are associated with increased risk of Crohn's disease. We used a candidate gene approach to identify a set of SNPs, located in a predicted regulatory region on chromosome 1q44 downstream of NLRP3 (previously known as CIAS1 and NALP3 ) that are associated with Crohn's disease. The associations were consistently replicated in four sample sets from individuals of European descent. In the combined analysis of all samples (710 father-mother-child trios, 239 cases and 107 controls), these SNPs were strongly associated with risk of Crohn's disease ( P combined = 3.49 × 10 −9 , odds ratio = 1.78, confidence interval = 1.47–2.16 for rs10733113), reaching a level consistent with the stringent significance thresholds imposed by whole-genome association studies. In addition, we observed significant associations between SNPs in the associated regions and NLRP3 expression and IL-1β production. Mutations in NLRP3 are known to be responsible for three rare autoinflammatory disorders 1 , 2 . These results suggest that the NLRP3 region is also implicated in the susceptibility of more common inflammatory diseases such as Crohn's disease.

Objectives The primary objective of this study was to use high-resolution micro-CT images to create accurate three-dimensional (3D) models of several intratemporal structures, and to compare several surgically important dimensions within the temporal bone. The secondary objective was to create a statistical shape model (SSM) of a dominant and non-dominant sigmoid sinus (SS) to provide a template for automated segmentation algorithms. Methods A free image processing software, 3D Slicer, was utilized to create three-dimensional reconstructions of the SS, jugular bulb (JB), facial nerve (FN), and external auditory canal (EAC) from micro-CT scans. The models were used to compare several clinically important dimensions between the dominant and non-dominant SS. Anatomic variability of the SS was also analyzed using SSMs generated using the Statismo software framework. Results Three-dimensional models from 38 temporal bones were generated and analyzed. Right dominance was observed in 74% of the paired SSs. All distances were significantly shorter on the dominant side ( p < 0.05), including: EAC – SS (dominant: 13.7 ± 3.4 mm; non-dominant: 15.3 ± 2.7 mm), FN – SS (dominant: 7.2 ± 1.8 mm; non-dominant: 8.1 ± 2.3 mm), 2nd genu FN – superior tip of JB (dominant: 8.7 ± 2.2 mm; non-dominant: 11.2 ± 2.6 mm), horizontal distance between the superior tip of JB – descending FN (dominant: 9.5 ± 2.3 mm; non-dominant: 13.2 ± 3.5 mm), and horizontal distance between the FN at the stylomastoid foramen – JB (dominant: 5.4 ± 2.2 mm; non-dominant: 7.7 ± 2.1). Analysis of the SSMs indicated that SS morphology is most variable at its junction with the transverse sinus, and least variable at the JB. Conclusions This is the first known study to investigate the anatomical variation and relationships of the SS using high resolution scans, 3D  models and statistical shape analysis. This analysis seeks to guide neurotological surgical approaches and provide a template for automated segmentation and surgical simulation.

The interplay between genetic and epigenetic variation is only partially understood. One form of epigenetic variation is methylation at CpG sites, which can be measured as methylation quantitative trait loci (meQTL). Here we report that in a panel of lymphocytes from 1,748 individuals, methylation levels at 1,919 CpG sites are correlated with at least one distal (trans) single-nucleotide polymorphism (SNP) (Po3.2 Â 10 À 13 ; FDRo5%). These trans-meQTLs include 1,657 SNP–CpG pairs from different chromosomes and 262 pairs from the same chromosome that are 41 Mb apart. Over 90% of these pairs are replicated (FDRo5%) in at least one of two independent data sets. Genomic loci harbouring trans-meQTLs are significantly enriched (Po0.001) for long non-coding transcripts (2.2-fold), known epigenetic regulators (2.3-fold), piwi-interacting RNA clusters (3.6-fold) and curated transcription factors (4.1-fold), including zinc-finger proteins (8.75-fold). Long-range epigenetic networks uncovered by this approach may be relevant to normal and disease states.

The systematic screening of the human genome for genetic variants that affect gene regulation should advance our fundamental understanding of phenotypic diversity and lead to the identification of alleles that modify disease risk. There are several challenges in localizing regulatory polymorphisms, including the wide spectrum of cis-acting regulatory mechanisms, the inconsistent effects of regulatory variants in different tissues, and the difficulty in isolating the causal variants that are in linkage disequilibrium with many other variants. We discuss the current state of knowledge and technologies used for mapping and characterizing genetic variation controlling human gene expression.