Genetics of gene expression in primary immune cells identifies cell type-specific master regulators and roles of HLA alleles

HLA-C Level Is Regulated by a Polymorphic Oct1 Binding Site in the HLA-C Promoter Region

Differential HLA-C levels influence several human diseases, but the mechanisms responsible are incompletely characterized. Using a validated prediction algorithm, we imputed HLA-C cell surface levels in 228 individuals from the 1000 Genomes dataset. We tested 68,726 SNPs within the MHC for association with HLA-C level. The HLA-C promoter region variant, rs2395471, 800 bp upstream of the transcription start site, gave the most significant association with HLA-C levels (p = 4.2 × 10-66). This imputed expression quantitative trait locus, termed impeQTL, was also shown to associate with HLA-C expression in a genome-wide association study of 273 donors in which HLA-C mRNA expression levels were determined by quantitative PCR (qPCR) (p = 1.8 × 10-20) and in two cohorts where HLA-C cell surface levels were determined directly by flow cytometry (n = 369 combined, p < 10-15). rs2395471 is located in an Oct1 transcription factor consensus binding site motif where the A allele is predicted to have higher affinity for Oct1 than the G allele. Mobility shift electrophoresis demonstrated that Oct1 binds to both alleles in vitro, but decreased HLA-C promoter activity was observed in a luciferase reporter assay for rs2395471_G relative to rs2395471_A on a fixed promoter background. The rs2395471 variant accounts for up to 36% of the explained variation of HLA-C level. These data strengthen our understanding of HLA-C transcriptional regulation and provide a basis for understanding the potential consequences of manipulating HLA-C levels therapeutically.

Lineage-Specific Genome Architecture Links Enhancers and Non-coding Disease Variants to Target Gene Promoters

Long-range interactions between regulatory elements and gene promoters play key roles in transcriptional regulation. The vast majority of interactions are uncharted, constituting a major missing link in understanding genome control. Here, we use promoter capture Hi-C to identify interacting regions of 31,253 promoters in 17 human primary hematopoietic cell types. We show that promoter interactions are highly cell type specific and enriched for links between active promoters and epigenetically marked enhancers. Promoter interactomes reflect lineage relationships of the hematopoietic tree, consistent with dynamic remodeling of nuclear architecture during differentiation. Interacting regions are enriched in genetic variants linked with altered expression of genes they contact, highlighting their functional role. We exploit this rich resource to connect non-coding disease variants to putative target promoters, prioritizing thousands of disease-candidate genes and implicating disease pathways. Our results demonstrate the power of primary cell promoter interactomes to reveal insights into genomic regulatory mechanisms underlying common diseases.

Concerted Genetic Function in Blood Traits

The hematopoietic system plays a major role in human health. Two studies by Astle et al. and Chen et al. published in this issue of Cell use genome-wide association and functional genomics approaches to provide deep insights into the role of genetic variants in hematological traits. We discuss these discoveries and future strategies toward completing our understanding of the genetic basis for variation in human traits.

Archaic Hominin Admixture Facilitated Adaptation to Out-of-Africa Environments

As modern humans dispersed from Africa throughout the world, they encountered and interbred with archaic hominins, including Neanderthals and Denisovans [1, 2]. Although genome-scale maps of introgressed sequences have been constructed [3-6], considerable gaps in knowledge remain about the functional, phenotypic, and evolutionary significance of archaic hominin DNA that persists in present-day individuals. Here, we describe a comprehensive set of analyses that identified 126 high-frequency archaic haplotypes as putative targets of adaptive introgression in geographically diverse populations. These loci are enriched for immune-related genes (such as OAS1/2/3, TLR1/6/10, and TNFAIP3) and also encompass genes (including OCA2 and BNC2) that influence skin pigmentation phenotypes. Furthermore, we leveraged existing and novel large-scale gene expression datasets to show many positively selected archaic haplotypes act as expression quantitative trait loci (eQTLs), suggesting that modulation of transcript abundance was a common mechanism facilitating adaptive introgression. Our results demonstrate that hybridization between modern and archaic hominins provided an important reservoir of advantageous alleles that enabled adaptation to out-of-Africa environments.

Transcriptome Profiling in Rat Inbred Strains and Experimental Cross Reveals Discrepant Genetic Architecture of Genome-Wide Gene Expression

To test the impact of genetic heterogeneity on cis- and trans-mediated mechanisms of gene expression regulation, we profiled the transcriptome of adipose tissue in 20 inbred congenic strains derived from diabetic Goto-Kakizaki (GK) rats and Brown-Norway (BN) controls, which contain well-defined blocks (1-183 Mb) of genetic polymorphisms, and in 123 genetically heterogeneous rats of an (GK × BN)F2 offspring. Within each congenic we identified 73-1351 differentially expressed genes (DEGs), only 7.7% of which mapped within the congenic blocks, and which may be regulated in cis The remainder localized outside the blocks, and therefore must be regulated in trans Most trans-regulated genes exhibited approximately twofold expression changes, consistent with monoallelic expression. Altered biological pathways were replicated between congenic strains sharing blocks of genetic polymorphisms, but polymorphisms at different loci also had redundant effects on transcription of common distant genes and pathways. We mapped 2735 expression quantitative trait loci (eQTL) in the F2 cross, including 26% predominantly cis-regulated genes, which validated DEGs in congenic strains. A hotspot of >300 eQTL in a 10 cM region of chromosome 1 was enriched in DEGs in a congenic strain. However, many DEGs among GK, BN and congenic strains did not replicate as eQTL in F2 hybrids, demonstrating distinct mechanisms of gene expression when alleles segregate in an outbred population or are fixed homozygous across the entire genome or in short genomic regions. Our analysis provides conceptual advances in our understanding of the complex architecture of genome expression and pathway regulation, and suggests a prominent impact of epistasis and monoallelic expression on gene transcription.

Capture Hi-C identifies a novel causal gene, IL20RA, in the pan-autoimmune genetic susceptibility region 6q23

BACKGROUND

The identification of causal genes from genome-wide association studies (GWAS) is the next important step for the translation of genetic findings into biologically meaningful mechanisms of disease and potential therapeutic targets. Using novel chromatin interaction detection techniques and allele specific assays in T and B cell lines, we provide compelling evidence that redefines causal genes at the 6q23 locus, one of the most important loci that confers autoimmunity risk.

RESULTS

Although the function of disease-associated non-coding single nucleotide polymorphisms (SNPs) at 6q23 is unknown, the association is generally assigned to TNFAIP3, the closest gene. However, the DNA fragment containing the associated SNPs interacts through chromatin looping not only with TNFAIP3, but also with IL20RA, located 680 kb upstream. The risk allele of the most likely causal SNP, rs6927172, is correlated with both a higher frequency of interactions and increased expression of IL20RA, along with a stronger binding of both the NFκB transcription factor and chromatin marks characteristic of active enhancers in T-cells.

CONCLUSIONS

Our results highlight the importance of gene assignment for translating GWAS findings into biologically meaningful mechanisms of disease and potential therapeutic targets; indeed, monoclonal antibody therapy targeting IL-20 is effective in the treatment of rheumatoid arthritis and psoriasis, both with strong GWAS associations to this region.

Decreased SMG7 expression associates with lupus-risk variants and elevated antinuclear antibody production

OBJECTIVES

Following up the systemic lupus erythematosus (SLE) genome-wide association studies (GWAS) identification of NMNAT2 at rs2022013, we fine-mapped its 150 kb flanking regions containing NMNAT2 and SMG7 in a 15 292 case-control multi-ancestry population and tested functions of identified variants.

METHODS

We performed genotyping using custom array, imputation by IMPUTE 2.1.2 and allele specific functions using quantitative real-time PCR and luciferase reporter transfections. SLE peripheral blood mononuclear cells (PBMCs) were cultured with small interfering RNAs to measure antinuclear antibody (ANA) and cyto/chemokine levels in supernatants using ELISA.

RESULTS

We confirmed association at NMNAT2 in European American (EA) and Amerindian/Hispanic ancestries, and identified independent signal at SMG7 tagged by rs2702178 in EA only (p=2.4×10-8, OR=1.23 (95% CI 1.14 to 1.32)). In complete linkage disequilibrium with rs2702178, rs2275675 in the promoter region robustly associated with SMG7 mRNA levels in multiple expression quantitative trait locus (eQTL) datasets. Its risk allele was dose-dependently associated with decreased SMG7 mRNA levels in PBMCs of 86 patients with SLE and 119 controls (p=1.1×10-3 and 6.8×10-8, respectively) and conferred reduced transcription activity in transfected HEK-293 (human embryonic kidney cell line) and Raji cells (p=0.0035 and 0.0037, respectively). As a critical component in the nonsense-mediated mRNA decay pathway, SMG7 could regulate autoantigens including ribonucleoprotein (RNP) and Smith (Sm). We showed SMG7 mRNA levels in PBMCs correlated inversely with ANA titres of patients with SLE (r=-0.31, p=0.01), and SMG7 knockdown increased levels of ANA IgG and chemokine (C-C motif) ligand 19 in SLE PBMCs (p=2.0×10-5 and 2.0×10-4, respectively).

CONCLUSION

We confirmed NMNAT2 and identified independent SMG7 association with SLE. The inverse relationship between levels of the risk allele-associated SMG7 mRNAs and ANA suggested the novel contribution of mRNA surveillance pathway to SLE pathogenesis.

Dynamics and Correlates of CD8 T-Cell Counts in Africans with Primary Human Immunodeficiency Virus Type 1 Infection

In individuals with HIV-1 infection, depletion of CD4⁺ T cells is often accompanied by a malfunction of CD8⁺ T cells that are persistently activated and/or exhausted. While the dynamics and correlates of CD4 counts have been well documented, the same does not apply to CD8 counts. Here, we examined the CD8 counts in a cohort of 497 Africans with primary HIV-1 infection evaluated in monthly to quarterly follow-up visits for up to 3 years in the absence of antiretroviral therapy. Statistical models revealed that (i) CD8 counts were relatively steady in the 3- to 36-month period of infection and similar between men and women; (ii) neither geography nor heterogeneity in the HIV-1 set-point viral load could account for the roughly 10-fold range of CD8 counts in the cohort (P > 0.25 in all tests); and (iii) factors independently associated with relatively high CD8 counts included demographics (age ≤ 40 years, adjusted P = 0.010) and several human leukocyte antigen class I (HLA-I) alleles, including HLA-A*03:01 (P = 0.013), B*15:10 (P = 0.007), and B*58:02 (P < 0.001). Multiple sensitivity analyses provided supporting evidence for these novel relationships. Overall, these findings suggest that factors associated with the CD8 count have little overlap with those previously reported for other HIV-1-related outcome measures, including viral load, CD4 count, and CD4/CD8 ratio.

IMPORTANCE

Longitudinal data from 497 HIV-1 seroconverters allowed us to systematically evaluate the dynamics and correlates of CD8⁺ T-cell counts during untreated primary HIV-1 infection in eastern and southern Africans. Our findings suggest that individuals with certain HLA-I alleles, including A*03 (exclusively A*03:01), persistently maintain relatively high CD8 counts following HIV-1 infection, a finding which may offer an intriguing explanation for the recently reported, negative association of A*03 with HIV-1-specific, broadly neutralizing antibody responses. In future studies, attention to HLA-I genotyping data may benefit in-depth understanding of both cellular and humoral immunity, as well as the intrinsic balances of these types of immunity, especially in settings where there is emerging evidence of antagonism between the two arms of adaptive immunity.

High-throughput allele-specific expression across 250 environmental conditions

Gene-by-environment (GxE) interactions determine common disease risk factors and biomedically relevant complex traits. However, quantifying how the environment modulates genetic effects on human quantitative phenotypes presents unique challenges. Environmental covariates are complex and difficult to measure and control at the organismal level, as found in GWAS and epidemiological studies. An alternative approach focuses on the cellular environment using in vitro treatments as a proxy for the organismal environment. These cellular environments simplify the organism-level environmental exposures to provide a tractable influence on subcellular phenotypes, such as gene expression. Expression quantitative trait loci (eQTL) mapping studies identified GxE interactions in response to drug treatment and pathogen exposure. However, eQTL mapping approaches are infeasible for large-scale analysis of multiple cellular environments. Recently, allele-specific expression (ASE) analysis emerged as a powerful tool to identify GxE interactions in gene expression patterns by exploiting naturally occurring environmental exposures. Here we characterized genetic effects on the transcriptional response to 50 treatments in five cell types. We discovered 1455 genes with ASE (FDR < 10%) and 215 genes with GxE interactions. We demonstrated a major role for GxE interactions in complex traits. Genes with a transcriptional response to environmental perturbations showed sevenfold higher odds of being found in GWAS. Additionally, 105 genes that indicated GxE interactions (49%) were identified by GWAS as associated with complex traits. Examples include GIPR–caffeine interaction and obesity and include LAMP3–selenium interaction and Parkinson disease. Our results demonstrate that comprehensive catalogs of GxE interactions are indispensable to thoroughly annotate genes and bridge epidemiological and genome-wide association studies.

From integrative genomics to systems genetics in the rat to link genotypes to phenotypes

Complementary to traditional gene mapping approaches used to identify the hereditary components of complex diseases, integrative genomics and systems genetics have emerged as powerful strategies to decipher the key genetic drivers of molecular pathways that underlie disease. Broadly speaking, integrative genomics aims to link cellular-level traits (such as mRNA expression) to the genome to identify their genetic determinants. With the characterization of several cellular-level traits within the same system, the integrative genomics approach evolved into a more comprehensive study design, called systems genetics, which aims to unravel the complex biological networks and pathways involved in disease, and in turn map their genetic control points. The first fully integrated systems genetics study was carried out in rats, and the results, which revealed conserved trans-acting genetic regulation of a pro-inflammatory network relevant to type 1 diabetes, were translated to humans. Many studies using different organisms subsequently stemmed from this example. The aim of this Review is to describe the most recent advances in the fields of integrative genomics and systems genetics applied in the rat, with a focus on studies of complex diseases ranging from inflammatory to cardiometabolic disorders. We aim to provide the genetics community with a comprehensive insight into how the systems genetics approach came to life, starting from the first integrative genomics strategies [such as expression quantitative trait loci (eQTLs) mapping] and concluding with the most sophisticated gene network-based analyses in multiple systems and disease states. Although not limited to studies that have been directly translated to humans, we will focus particularly on the successful investigations in the rat that have led to primary discoveries of genes and pathways relevant to human disease.

Gender Differences in Adipocyte Metabolism and Liver Cancer Progression

Liver cancer is the third most common cancer type and the second leading cause of deaths in men. Large population studies have demonstrated remarkable gender disparities in the incidence and the cumulative risk of liver cancer. A number of emerging risk factors regarding metabolic alterations associated with obesity, diabetes and dyslipidemia have been ascribed to the progression of non-alcoholic fatty liver diseases (NAFLD) and ultimately liver cancer. The deregulation of fat metabolism derived from excessive insulin, glucose, and lipid promotes cancer-causing inflammatory signaling and oxidative stress, which eventually triggers the uncontrolled hepatocellular proliferation. This review presents the current standing on the gender differences in body fat compositions and their mechanistic linkage with the development of NAFLD-related liver cancer, with an emphasis on genetic, epigenetic and microRNA control. The potential roles of sex hormones in instructing adipocyte metabolic programs may help unravel the mechanisms underlying gender dimorphism in liver cancer and identify the metabolic targets for disease management.

Immunoseq: the identification of functionally relevant variants through targeted capture and sequencing of active regulatory regions in human immune cells

Background

The observation that the genetic variants identified in genome-wide association studies (GWAS) frequently lie in non-coding regions of the genome that contain cis-regulatory elements suggests that altered gene expression underlies the development of many complex traits. In order to efficiently make a comprehensive assessment of the impact of non-coding genetic variation in immune related diseases we emulated the whole-exome sequencing paradigm and developed a custom capture panel for the known DNase I hypersensitive site (DHS) in immune cells – “Immunoseq”.

Results

We performed Immunoseq in 30 healthy individuals where we had existing transcriptome data from T cells. We identified a large number of novel non-coding variants in these samples. Relying on allele specific expression measurements, we also showed that our selected capture regions are enriched for functional variants that have an impact on differential allelic gene expression. The results from a replication set with 180 samples confirmed our observations.

Conclusions

We show that Immunoseq is a powerful approach to detect novel rare variants in regulatory regions. We also demonstrate that these novel variants have a potential functional role in immune cells.

Electronic supplementary material

The online version of this article (doi:10.1186/s12920-016-0220-7) contains supplementary material, which is available to authorized users.

Characterization of candidate genes in inflammatory bowel disease-associated risk loci

GWAS have linked SNPs to risk of inflammatory bowel disease (IBD), but a systematic characterization of disease-associated genes has been lacking. Prior studies utilized microarrays that did not capture many genes encoded within risk loci or defined expression quantitative trait loci (eQTLs) using peripheral blood, which is not the target tissue in IBD. To address these gaps, we sought to characterize the expression of IBD-associated risk genes in disease-relevant tissues and in the setting of active IBD. Terminal ileal (TI) and colonic mucosal tissues were obtained from patients with Crohn's disease or ulcerative colitis and from healthy controls. We developed a NanoString code set to profile 678 genes within IBD risk loci. A subset of patients and controls were genotyped for IBD-associated risk SNPs. Analyses included differential expression and variance analysis, weighted gene coexpression network analysis, and eQTL analysis. We identified 116 genes that discriminate between healthy TI and colon samples and uncovered patterns in variance of gene expression that highlight heterogeneity of disease. We identified 107 coexpressed gene pairs for which transcriptional regulation is either conserved or reversed in an inflammation-independent or -dependent manner. We demonstrate that on average approximately 60% of disease-associated genes are differentially expressed in inflamed tissue. Last, we identified eQTLs with either genotype-only effects on expression or an interaction effect between genotype and inflammation. Our data reinforce tissue specificity of expression in disease-associated candidate genes, highlight genes and gene pairs that are regulated in disease-relevant tissue and inflammation, and provide a foundation to advance the understanding of IBD pathogenesis.

Genome-wide association meta-analysis in Chinese and European individuals identifies ten new loci associated with systemic lupus erythematosus

Systemic lupus erythematosus (SLE; OMIM 152700) is a genetically complex autoimmune disease. Genome-wide association studies (GWASs) have identified more than 50 loci as robustly associated with the disease in single ancestries, but genome-wide transancestral studies have not been conducted. We combined three GWAS data sets from Chinese (1,659 cases and 3,398 controls) and European (4,036 cases and 6,959 controls) populations. A meta-analysis of these studies showed that over half of the published SLE genetic associations are present in both populations. A replication study in Chinese (3,043 cases and 5,074 controls) and European (2,643 cases and 9,032 controls) subjects found ten previously unreported SLE loci. Our study provides further evidence that the majority of genetic risk polymorphisms for SLE are contained within the same regions across both populations. Furthermore, a comparison of risk allele frequencies and genetic risk scores suggested that the increased prevalence of SLE in non-Europeans (including Asians) has a genetic basis.

Four Susceptibility Loci for Gallstone Disease Identified in a Meta-analysis of Genome-Wide Association Studies

BACKGROUND & AIMS

A genome-wide association study (GWAS) of 280 cases identified the hepatic cholesterol transporter ABCG8 as a locus associated with risk for gallstone disease, but findings have not been reported from any other GWAS of this phenotype. We performed a large-scale, meta-analysis of GWASs of individuals of European ancestry with available prior genotype data, to identify additional genetic risk factors for gallstone disease.

METHODS

We obtained per-allele odds ratio (OR) and standard error estimates using age- and sex-adjusted logistic regression models within each of the 10 discovery studies (8720 cases and 55,152 controls). We performed an inverse variance weighted, fixed-effects meta-analysis of study-specific estimates to identify single-nucleotide polymorphisms that were associated independently with gallstone disease. Associations were replicated in 6489 cases and 62,797 controls.

RESULTS

We observed independent associations for 2 single-nucleotide polymorphisms at the ABCG8 locus: rs11887534 (OR, 1.69; 95% confidence interval [CI], 1.54-1.86; P = 2.44 × 10(-60)) and rs4245791 (OR, 1.27; P = 1.90 × 10(-34)). We also identified and/or replicated associations for rs9843304 in TM4SF4 (OR, 1.12; 95% CI, 1.08-1.16; P = 6.09 × 10(-11)), rs2547231 in SULT2A1 (encodes a sulfoconjugation enzyme that acts on hydroxysteroids and cholesterol-derived sterol bile acids) (OR, 1.17; 95% CI, 1.12-1.21; P = 2.24 × 10(-10)), rs1260326 in glucokinase regulatory protein (OR, 1.12; 95% CI, 1.07-1.17; P = 2.55 × 10(-10)), and rs6471717 near CYP7A1 (encodes an enzyme that catalyzes conversion of cholesterol to primary bile acids) (OR, 1.11; 95% CI, 1.08-1.15; P = 8.84 × 10(-9)). Among individuals of African American and Hispanic American ancestry, rs11887534 and rs4245791 were associated positively with gallstone disease risk, whereas the association for the rs1260326 variant was inverse.

CONCLUSIONS

In this large-scale GWAS of gallstone disease, we identified 4 loci in genes that have putative functions in cholesterol metabolism and transport, and sulfonylation of bile acids or hydroxysteroids.

Targeted genomic analysis reveals widespread autoimmune disease association with regulatory variants in the TNF superfamily cytokine signalling network

BACKGROUND

Tumour necrosis factor (TNF) superfamily cytokines and their receptors regulate diverse immune system functions through a common set of signalling pathways. Genetic variants in and expression of individual TNF superfamily cytokines, receptors and signalling proteins have been associated with autoimmune and inflammatory diseases, but their interconnected biology has been largely unexplored.

METHODS

We took a hypothesis-driven approach using available genome-wide datasets to identify genetic variants regulating gene expression in the TNF superfamily cytokine signalling network and the association of these variants with autoimmune and autoinflammatory disease. Using paired gene expression and genetic data, we identified genetic variants associated with gene expression, expression quantitative trait loci (eQTLs), in four peripheral blood cell subsets. We then examined whether eQTLs were dependent on gene expression level or the presence of active enhancer chromatin marks. Using these eQTLs as genetic markers of the TNF superfamily signalling network, we performed targeted gene set association analysis in eight autoimmune and autoinflammatory disease genome-wide association studies.

RESULTS

Comparison of TNF superfamily network gene expression and regulatory variants across four leucocyte subsets revealed patterns that differed between cell types. eQTLs for genes in this network were not dependent on absolute gene expression levels and were not enriched for chromatin marks of active enhancers. By examining autoimmune disease risk variants among our eQTLs, we found that risk alleles can be associated with either increased or decreased expression of co-stimulatory TNF superfamily cytokines, receptors or downstream signalling molecules. Gene set disease association analysis revealed that eQTLs for genes in the TNF superfamily pathway were associated with six of the eight autoimmune and autoinflammatory diseases examined, demonstrating associations beyond single genome-wide significant hits.

CONCLUSIONS

This systematic analysis of the influence of regulatory genetic variants in the TNF superfamily network reveals widespread and diverse roles for these cytokines in susceptibility to a number of immune-mediated diseases.

Genetics and immunity in the era of single-cell genomics

Recent developments in the field of single-cell genomics (SCG) are changing our understanding of how functional phenotypes of cell populations emerge from the behaviour of individual cells. Some of the applications of SCG include the discovery of new gene networks and novel cell subpopulations, fine mapping of transcription kinetics, and the relationships between cell clonality and their functional phenotypes. Immunology is one of the fields that is benefiting the most from such advancements, providing us with completely new insights into mammalian immunity. In this review, we start by covering new immunological insights originating from the use of single-cell genomic tools, specifically single-cell RNA-sequencing. Furthermore, we discuss how new genetic study designs are starting to explain inter-individual variation in the immune response. We conclude with a perspective on new multi-omics technologies capable of integrating several readouts from the same single cell and how such techniques might push our biological understanding of mammalian immunity to a new level.

Identification of STOML2 as a putative novel asthma risk gene associated with IL6R

BACKGROUND

Functional variants in the interleukin-6 receptor gene (IL6R) are associated with asthma risk. We hypothesized that genes co-expressed with IL6R might also be regulated by genetic polymorphisms that are associated with asthma risk. The aim of this study was to identify such genes.

METHODS

To identify genes whose expression was correlated with that of IL6R, we analyzed gene expression levels generated for 373 human lymphoblastoid cell lines by the Geuvadis consortium and for 38 hematopoietic cell types by the Differentiation Map Portal (DMAP) project. Genes correlated with IL6R were then screened for nearby single nucleotide polymorphisms (SNPs) that were significantly associated with both variation in gene expression levels (eSNPs) and asthma risk.

RESULTS

We identified 90 genes with expression levels correlated with those of IL6R and that also had a nearby eSNP associated with disease risk in a published asthma GWAS (N = 20 776). For 16 (18%) genes, the association between the eSNP and asthma risk replicated with the same direction of effect in a further independent published asthma GWAS (N = 27 378). Among the top replicated associations (FDR < 0.05) were eSNPs for four known (IL18R1, IL18RAP, BCL6, and STAT6) and one putative novel asthma risk gene, stomatin-like protein 2 (STOML2). The expression of STOML2 was negatively correlated with IL6R, while eSNPs that increased the expression of STOML2 were associated with an increased asthma risk.

CONCLUSION

The expression of STOML2, a gene that plays a key role in mitochondrial function and T-cell activation, is associated with both IL-6 signaling and asthma risk.

Identification of Tissue-Specific Protein-Coding and Noncoding Transcripts across 14 Human Tissues Using RNA-seq

Many diseases and adverse drug reactions exhibit tissue specificity. To better understand the tissue-specific expression characteristics of transcripts in different human tissues, we deeply sequenced RNA samples from 14 different human tissues. After filtering many lowly expressed transcripts, 24,729 protein-coding transcripts and 1,653 noncoding transcripts were identified. By analyzing highly expressed tissue-specific protein-coding transcripts (TSCTs) and noncoding transcripts (TSNTs), we found that testis expressed the highest numbers of TSCTs and TSNTs. Brain, monocytes, ovary, and heart expressed more TSCTs than the rest tissues, whereas brain, placenta, heart, and monocytes expressed more TSNTs than other tissues. Co-expression network constructed based on the TSCTs and TSNTs showed that each hub TSNT was co-expressed with several TSCTs, allowing functional annotation of TSNTs. Important biological processes and KEGG pathways highly related to the specific functions or diseases of each tissue were enriched with the corresponding TSCTs. These TSCTs and TSNTs may participate in the tissue-specific physiological or pathological processes. Our study provided a unique data set and systematic analysis of expression characteristics and functions of both TSCTs and TSNTs based on 14 distinct human tissues, and could facilitate future investigation of the mechanisms behind tissue-specific diseases and adverse drug reactions.

In vitro transdifferentiation of human peripheral blood mononuclear cells to photoreceptor-like cells

Direct reprogramming is a promising, simple and low-cost approach to generate target cells from somatic cells without using induced pluripotent stem cells. Recently, peripheral blood mononuclear cells (PBMCs) have attracted considerable attention as a somatic cell source for reprogramming. As a cell source, PBMCs have an advantage over dermal fibroblasts with respect to the ease of collecting tissues. Based on our studies involving generation of photosensitive photoreceptor cells from human iris cells and human dermal fibroblasts by transduction of photoreceptor-related transcription factors via retrovirus vectors, we transduced these transcription factors into PBMCs via Sendai virus vectors. We found that retinal disease-related genes were efficiently detected in CRX-transduced cells, most of which are crucial to photoreceptor functions. In functional studies, a light-induced inward current was detected in some CRX-transduced cells. Moreover, by modification of the culture conditions including additional transduction of RAX1 and NEUROD1, we found a greater variety of retinal disease-related genes than that observed in CRX-transduced PBMCs. These data suggest that CRX acts as a master control gene for reprogramming PBMCs into photoreceptor-like cells and that our induced photoreceptor-like cells might contribute to individualized drug screening and disease modeling of inherited retinal degeneration.

Genetic susceptibility to rheumatoid arthritis and its implications for novel drug discovery

INTRODUCTION

Over 100 susceptibility loci have now been identified for rheumatoid arthritis (RA), several of which are already the targets of approved RA therapies providing proof of concept for the use of genetics in novel drug development for RA. Determining how these loci contribute to disease will be key to elucidating the mechanisms driving disease development, which has the potential for major impact on therapeutic development.

AREAS COVERED

Here the authors review the use of genetics in drug discovery, including the use of 'omics' data to prioritise potential drug targets at susceptibility loci using RA as an exemplar. They discuss the current state of RA genetics its impact on stratified medicine, and how the findings from RA genetics studies can be used to inform drug discovery.

EXPERT OPINION

It is anticipated that functional characterisation of disease variants will provide biological validation of a gene as a drug target, providing safer targets, with an increased likelihood of efficacy. In the future, techniques such as genome editing may represent a plausible option for RA therapy. Technologies such as genome-wide chromatin conformation capture Hi-C and CRISPR will be crucial to inform our understanding of how diseases develop and in developing new treatments.

Polymorphism in a lincRNA Associates with a Doubled Risk of Pneumococcal Bacteremia in Kenyan Children

Bacteremia (bacterial bloodstream infection) is a major cause of illness and death in sub-Saharan Africa but little is known about the role of human genetics in susceptibility. We conducted a genome-wide association study of bacteremia susceptibility in more than 5,000 Kenyan children as part of the Wellcome Trust Case Control Consortium 2 (WTCCC2). Both the blood-culture-proven bacteremia case subjects and healthy infants as controls were recruited from Kilifi, on the east coast of Kenya. Streptococcus pneumoniae is the most common cause of bacteremia in Kilifi and was thus the focus of this study. We identified an association between polymorphisms in a long intergenic non-coding RNA (lincRNA) gene (AC011288.2) and pneumococcal bacteremia and replicated the results in the same population (p combined = 1.69 × 10(-9); OR = 2.47, 95% CI = 1.84-3.31). The susceptibility allele is African specific, derived rather than ancestral, and occurs at low frequency (2.7% in control subjects and 6.4% in case subjects). Our further studies showed AC011288.2 expression only in neutrophils, a cell type that is known to play a major role in pneumococcal clearance. Identification of this novel association will further focus research on the role of lincRNAs in human infectious disease.

Genome-wide search followed by replication reveals genetic interaction of CD80 and ALOX5AP associated with systemic lupus erythematosus in Asian populations

OBJECTIVES

Genetic interaction has been considered as a hallmark of the genetic architecture of systemic lupus erythematosus (SLE). Based on two independent genome-wide association studies (GWAS) on Chinese populations, we performed a genome-wide search for genetic interactions contributing to SLE susceptibility.

METHODS

The study involved a total of 1 659 cases and 3 398 controls in the discovery stage and 2 612 cases and 3 441 controls in three cohorts for replication. Logistic regression and multifactor dimensionality reduction were used to search for genetic interaction.

RESULTS

Interaction of CD80 (rs2222631) and ALOX5AP (rs12876893) was found to be significantly associated with SLE (OR_int=1.16, P_int_all=7.7E-04 at false discovery rate<0.05). Single nuclear polymorphism rs2222631 was found associated with SLE with genome-wide significance (P_all=4.5E-08, OR=0.86) and is independent of rs6804441 in CD80, whose association was reported previously. Significant correlation was observed between expression of these two genes in healthy controls and SLE cases, together with differential expression of these genes between cases and controls, observed from individuals from the Hong Kong cohort. Genetic interactions between BLK (rs13277113) and DDX6 (rs4639966), and between TNFSF4 (rs844648) and PXK (rs6445975) were also observed in both GWAS data sets.

CONCLUSIONS

Our study represents the first genome-wide evaluation of epistasis interactions on SLE and the findings suggest interactions and independent variants may help partially explain missing heritability for complex diseases.

Integrative genomic deconvolution of rheumatoid arthritis GWAS loci into gene and cell type associations

Background

Although genome-wide association studies (GWAS) have identified over 100 genetic loci associated with rheumatoid arthritis (RA), our ability to translate these results into disease understanding and novel therapeutics is limited. Most RA GWAS loci reside outside of protein-coding regions and likely affect distal transcriptional enhancers. Furthermore, GWAS do not identify the cell types where the associated causal gene functions. Thus, mapping the transcriptional regulatory roles of GWAS hits and the relevant cell types will lead to better understanding of RA pathogenesis.

Results

We combine the whole-genome sequences and blood transcription profiles of 377 RA patients and identify over 6000 unique genes with expression quantitative trait loci (eQTLs). We demonstrate the quality of the identified eQTLs through comparison to non-RA individuals. We integrate the eQTLs with immune cell epigenome maps, RA GWAS risk loci, and adjustment for linkage disequilibrium to propose target genes of immune cell enhancers that overlap RA risk loci. We examine 20 immune cell epigenomes and perform a focused analysis on primary monocytes, B cells, and T cells.

Conclusions

We highlight cell-specific gene associations with relevance to RA pathogenesis including the identification of FCGR2B in B cells as possessing both intragenic and enhancer regulatory GWAS hits. We show that our RA patient cohort derived eQTL network is more informative for studying RA than that from a healthy cohort. While not experimentally validated here, the reported eQTLs and cell type-specific RA risk associations can prioritize future experiments with the goal of elucidating the regulatory mechanisms behind genetic risk associations.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-016-0948-6) contains supplementary material, which is available to authorized users.

RNA splicing is a primary link between genetic variation and disease

Noncoding variants play a central role in the genetics of complex traits, but we still lack a full understanding of the molecular pathways through which they act. We quantified the contribution of cis-acting genetic effects at all major stages of gene regulation from chromatin to proteins, in Yoruba lymphoblastoid cell lines (LCLs). About ~65% of expression quantitative trait loci (eQTLs) have primary effects on chromatin, whereas the remaining eQTLs are enriched in transcribed regions. Using a novel method, we also detected 2893 splicing QTLs, most of which have little or no effect on gene-level expression. These splicing QTLs are major contributors to complex traits, roughly on a par with variants that affect gene expression levels. Our study provides a comprehensive view of the mechanisms linking genetic variation to variation in human gene regulation.

Genome-wide association study identifies five new susceptibility loci for primary angle closure glaucoma

Primary angle closure glaucoma (PACG) is a major cause of blindness worldwide. We conducted a genome-wide association study (GWAS) followed by replication in a combined total of 10,503 PACG cases and 29,567 controls drawn from 24 countries across Asia, Australia, Europe, North America, and South America. We observed significant evidence of disease association at five new genetic loci upon meta-analysis of all patient collections. These loci are at EPDR1 rs3816415 (odds ratio (OR) = 1.24, P = 5.94 × 10(-15)), CHAT rs1258267 (OR = 1.22, P = 2.85 × 10(-16)), GLIS3 rs736893 (OR = 1.18, P = 1.43 × 10(-14)), FERMT2 rs7494379 (OR = 1.14, P = 3.43 × 10(-11)), and DPM2-FAM102A rs3739821 (OR = 1.15, P = 8.32 × 10(-12)). We also confirmed significant association at three previously described loci (P < 5 × 10(-8) for each sentinel SNP at PLEKHA7, COL11A1, and PCMTD1-ST18), providing new insights into the biology of PACG.

A rare nonsynonymous variant in the lipid metabolic gene HELZ2 related to primary biliary cirrhosis in Chinese Han

Background

Several genome-wide association studies of primary biliary cirrhosis (PBC) in European and Japanese origins have shown significant association of dozens of genetic loci contributive to the susceptibility of PBC. Most of the loci were related to immune response pathway. In this study, we tested whether the lipid metabolic gene HELZ2 was associated with the pathogenesis of PBC.

Methods

In 586 PBC cases (358 in case 1 group and 201 in case 2 group) and 726 healthy controls of Chinese Han, six nonsynonymous SNPs were genotyped by MassArray iPLEX. The same control were used for the two groups of PBC cases. Allele frequencies were calculated by χ² test based on 2 × 2 contingency tables. All data were analyzed using the PLINK tool set. The odds ratio (OR) and 95 % confidence interval (95 % CI) were calculated, and p values (corrected for multiple testing by Bonferroni adjustment) less than 0.05 were considered statistically significant.

Results

The A allele of rs79267778 was significantly associated with PBC (OR_combined = 4.204 [1.670–10.582], p_combined = 1.87E−04). It changed the amino acid at position 1904 (NM_001037335) from Threonine (ACG) to Methionine (ATG). This site was highly conserved in mammals and predicted to be POSSIBLY DAMAGING with a score of 0.469 by PolyPhen-2. It’s further predicted that T1904 M could INCREASE the protein stability with a confidence at 25.18 % under the condition of pH 7.0 and 37 °C.

Conclusion

The result was the first time to show evidence of the lipid metabolic gene HELZ2 related to autoimmune disease, at least in PBC of Chinese Han.

The importance of p53 pathway genetics in inherited and somatic cancer genomes

Decades of research have shown that mutations in the p53 stress response pathway affect the incidence of diverse cancers more than mutations in other pathways. However, most evidence is limited to somatic mutations and rare inherited mutations. Using newly abundant genomic data, we demonstrate that commonly inherited genetic variants in the p53 pathway also affect the incidence of a broad range of cancers more than variants in other pathways. The cancer-associated single nucleotide polymorphisms (SNPs) of the p53 pathway have strikingly similar genetic characteristics to well-studied p53 pathway cancer-causing somatic mutations. Our results enable insights into p53-mediated tumour suppression in humans and into p53 pathway-based cancer surveillance and treatment strategies.

Systematic identification of genetic influences on methylation across the human life course

Background

The influence of genetic variation on complex diseases is potentially mediated through a range of highly dynamic epigenetic processes exhibiting temporal variation during development and later life. Here we present a catalogue of the genetic influences on DNA methylation (methylation quantitative trait loci (mQTL)) at five different life stages in human blood: children at birth, childhood, adolescence and their mothers during pregnancy and middle age.

Results

We show that genetic effects on methylation are highly stable across the life course and that developmental change in the genetic contribution to variation in methylation occurs primarily through increases in environmental or stochastic effects. Though we map a large proportion of the cis-acting genetic variation, a much larger component of genetic effects influencing methylation are acting in trans. However, only 7 % of discovered mQTL are trans-effects, suggesting that the trans component is highly polygenic. Finally, we estimate the contribution of mQTL to variation in complex traits and infer that methylation may have a causal role consistent with an infinitesimal model in which many methylation sites each have a small influence, amounting to a large overall contribution.

Conclusions

DNA methylation contains a significant heritable component that remains consistent across the lifespan. Our results suggest that the genetic component of methylation may have a causal role in complex traits. The database of mQTL presented here provide a rich resource for those interested in investigating the role of methylation in disease.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-016-0926-z) contains supplementary material, which is available to authorized users.

Insight into Genotype-Phenotype Associations through eQTL Mapping in Multiple Cell Types in Health and Immune-Mediated Disease

Genome-wide association studies (GWAS) have transformed our understanding of the genetics of complex traits such as autoimmune diseases, but how risk variants contribute to pathogenesis remains largely unknown. Identifying genetic variants that affect gene expression (expression quantitative trait loci, or eQTLs) is crucial to addressing this. eQTLs vary between tissues and following in vitro cellular activation, but have not been examined in the context of human inflammatory diseases. We performed eQTL mapping in five primary immune cell types from patients with active inflammatory bowel disease (n = 91), anti-neutrophil cytoplasmic antibody-associated vasculitis (n = 46) and healthy controls (n = 43), revealing eQTLs present only in the context of active inflammatory disease. Moreover, we show that following treatment a proportion of these eQTLs disappear. Through joint analysis of expression data from multiple cell types, we reveal that previous estimates of eQTL immune cell-type specificity are likely to have been exaggerated. Finally, by analysing gene expression data from multiple cell types, we find eQTLs not previously identified by database mining at 34 inflammatory bowel disease-associated loci. In summary, this parallel eQTL analysis in multiple leucocyte subsets from patients with active disease provides new insights into the genetic basis of immune-mediated diseases.

The human immune system has evolved to protect us from infection and cancer, whilst avoiding damage to healthy tissue. If this complex system goes wrong, immune cells may cause inappropriate inflammation and damage, resulting in clinical disease. Examples include inflammatory bowel disease and autoimmune vasculitis, characterised by inflammation in the gut and blood vessels respectively. Genetic studies have identified many variants in our DNA code that predispose to such immune-mediated diseases. The majority of these variants lie outside protein-coding regions, and so how they influence disease risk remains largely unclear. Examining how genetic variants affect gene expression can help bridge this gap in our knowledge, but these effects are highly dependent on the cellular or environmental context such as tissue type or cellular activation status. We investigated the genetic control of gene expression in five white blood cell subtypes taken from patients with active inflammatory bowel disease and autoimmune vasculitis, and from healthy controls. We report the novel observation of distinct variants that only affect gene expression in patients with active inflammatory disease, and show that these effects can disappear following treatment. These findings provide new insights into the genetic basis of important immune-mediated diseases.

Risk Genes of Inflammatory Bowel Disease in Asia: What Are the Most Important Pathways Affected?

Genetic factors play an important role in the pathogenesis of inflammatory bowel disease (IBD), and IBD is now recognized as a complex disease that results from interplay between genetic and environment factors. To date, over 160 IBD-susceptible loci have been identified using genome-wide association studies (GWAS). The risk genes identified in these studies are involved in various pathways in innate and adaptive immune response such as innate bacterial sensing, autophagy and interleukin-23 receptor/T-helper cell 17 pathway. It was initially believed that the genetic backgrounds of Asian IBD patients differ from that of other populations. Recent GWAS and meta-analysis found that there is pervasive sharing of risk loci between the East and West. Overlapping risk genes between populations of different ancestries indicate that pathways underlying the etiology of IBD may be common between Asia and other areas. However, the importance of individual pathways may be different in Asia from the Western countries. Identifying the most important pathways affected in Asian IBD patients may provide a better understanding of pathogenesis of IBD in Asia and improve the clinical management of the patients.

Analysis of five chronic inflammatory diseases identifies 27 new associations and highlights disease-specific patterns at shared loci

We simultaneously investigated the genetic landscape of ankylosing spondylitis, Crohn's disease, psoriasis, primary sclerosing cholangitis and ulcerative colitis to investigate pleiotropy and the relationship between these clinically related diseases. Using high-density genotype data from more than 86,000 individuals of European ancestry, we identified 244 independent multidisease signals, including 27 new genome-wide significant susceptibility loci and 3 unreported shared risk loci. Complex pleiotropy was supported when contrasting multidisease signals with expression data sets from human, rat and mouse together with epigenetic and expressed enhancer profiles. The comorbidities among the five immune diseases were best explained by biological pleiotropy rather than heterogeneity (a subgroup of cases genetically identical to those with another disease, possibly owing to diagnostic misclassification, molecular subtypes or excessive comorbidity). In particular, the strong comorbidity between primary sclerosing cholangitis and inflammatory bowel disease is likely the result of a unique disease, which is genetically distinct from classical inflammatory bowel disease phenotypes.

Understanding Celiac Disease by Genomics

Celiac disease (CeD) is a complex immune-mediated disease. Genetic studies have implicated 43 predisposing loci that collectively explain some 50% of the genetic variance in CeD. More than ∼90% of CeD-associated single nucleotide polymorphisms (SNPs) localize to the non-coding genome, which we need to better understand to translate genetic knowledge into clinical practice. New genomic technologies and resources are permitting a systematic analysis of the functional elements in the non-coding part of the genome. Here we explain how investigating the regulatory and epigenomic landscape will help to pinpoint the cell types involved in CeD, and the driver genes and gene regulatory networks that are affected by CeD-associated SNPs.

Autoimmune diseases - connecting risk alleles with molecular traits of the immune system

Genome-wide strategies have driven the discovery of more than 300 susceptibility loci for autoimmune diseases. However, for almost all loci, understanding of the mechanisms leading to autoimmunity remains limited, and most variants that are likely to be causal are in non-coding regions of the genome. A critical next step will be to identify the in vivo and ex vivo immunophenotypes that are affected by risk variants. To do this, key cell types and cell states that are implicated in autoimmune diseases will need to be defined. Functional genomic annotations from these cell types and states can then be used to resolve candidate genes and causal variants. Together with longitudinal studies, this approach may yield pivotal insights into how autoimmunity is triggered.

Modelling local gene networks increases power to detect trans-acting genetic effects on gene expression

Expression quantitative trait loci (eQTL) mapping is a widely used tool to study the genetics of gene expression. Confounding factors and the burden of multiple testing limit the ability to map distal trans eQTLs, which is important to understand downstream genetic effects on genes and pathways. We propose a two-stage linear mixed model that first learns local directed gene-regulatory networks to then condition on the expression levels of selected genes. We show that this covariate selection approach controls for confounding factors and regulatory context, thereby increasing eQTL detection power and improving the consistency between studies. GNet-LMM is available at: https://github.com/PMBio/GNetLMM.

Systematic Evaluation of Genes and Genetic Variants Associated with Type 1 Diabetes Susceptibility

Genome-wide association studies have found >60 loci that confer genetic susceptibility to type 1 diabetes (T1D). Many of these are defined only by anonymous single nucleotide polymorphisms: the underlying causative genes, as well as the molecular bases by which they mediate susceptibility, are not known. Identification of how these variants affect the complex mechanisms contributing to the loss of tolerance is a challenge. In this study, we performed systematic analyses to characterize these variants. First, all known genes in strong linkage disequilibrium (r(2) > 0.8) with the reported single nucleotide polymorphisms for each locus were tested for commonly occurring nonsynonymous variations. We found only a total of 22 candidate genes at 16 T1D loci with common nonsynonymous alleles. Next, we performed functional studies to examine the effect of non-HLA T1D risk alleles on regulating expression levels of genes in four different cell types: EBV-transformed B cell lines (resting and 6 h PMA stimulated) and purified CD4(+) and CD8(+) T cells. We mapped cis-acting expression quantitative trait loci and found 24 non-HLA loci that affected the expression of 31 transcripts significantly in at least one cell type. Additionally, we observed 25 loci that affected 38 transcripts in trans. In summary, our systems genetics analyses defined the effect of T1D risk alleles on levels of gene expression and provide novel insights into the complex genetics of T1D, suggesting that most of the T1D risk alleles mediate their effect by influencing expression of multiple nearby genes.

Genomic landscape of the individual host response and outcomes in sepsis: a prospective cohort study

BACKGROUND

Effective targeted therapy for sepsis requires an understanding of the heterogeneity in the individual host response to infection. We investigated this heterogeneity by defining interindividual variation in the transcriptome of patients with sepsis and related this to outcome and genetic diversity.

METHODS

We assayed peripheral blood leucocyte global gene expression for a prospective discovery cohort of 265 adult patients admitted to UK intensive care units with sepsis due to community-acquired pneumonia and evidence of organ dysfunction. We then validated our findings in a replication cohort consisting of a further 106 patients. We mapped genomic determinants of variation in gene transcription between patients as expression quantitative trait loci (eQTL).

FINDINGS

We discovered that following admission to intensive care, transcriptomic analysis of peripheral blood leucocytes defines two distinct sepsis response signatures (SRS1 and SRS2). The presence of SRS1 (detected in 108 [41%] patients in discovery cohort) identifies individuals with an immunosuppressed phenotype that included features of endotoxin tolerance, T-cell exhaustion, and downregulation of human leucocyte antigen (HLA) class II. SRS1 was associated with higher 14 day mortality than was SRS2 (discovery cohort hazard ratio (HR) 2·4, 95% CI 1·3-4·5, p=0·005; validation cohort HR 2·8, 95% CI 1·5-5·1, p=0·0007). We found that a predictive set of seven genes enabled the classification of patients as SRS1 or SRS2. We identified cis-acting and trans-acting eQTL for key immune and metabolic response genes and sepsis response networks. Sepsis eQTL were enriched in endotoxin-induced epigenetic marks and modulated the individual host response to sepsis, including effects specific to SRS group. We identified regulatory genetic variants involving key mediators of gene networks implicated in the hypoxic response and the switch to glycolysis that occurs in sepsis, including HIF1α and mTOR, and mediators of endotoxin tolerance, T-cell activation, and viral defence.

INTERPRETATION

Our integrated genomics approach advances understanding of heterogeneity in sepsis by defining subgroups of patients with different immune response states and prognoses, as well as revealing the role of underlying genetic variation. Our findings provide new insights into the pathogenesis of sepsis and create opportunities for a precision medicine approach to enable targeted therapeutic intervention to improve sepsis outcomes.

FUNDING

European Commission, Medical Research Council (UK), and the Wellcome Trust.

Regulatory polymorphisms modulate the expression of HLA class II molecules and promote autoimmunity

Targeted sequencing of sixteen SLE risk loci among 1349 Caucasian cases and controls produced a comprehensive dataset of the variations causing susceptibility to systemic lupus erythematosus (SLE). Two independent disease association signals in the HLA-D region identified two regulatory regions containing 3562 polymorphisms that modified thirty-seven transcription factor binding sites. These extensive functional variations are a new and potent facet of HLA polymorphism. Variations modifying the consensus binding motifs of IRF4 and CTCF in the XL9 regulatory complex modified the transcription of HLA-DRB1, HLA-DQA1 and HLA-DQB1 in a chromosome-specific manner, resulting in a 2.5-fold increase in the surface expression of HLA-DR and DQ molecules on dendritic cells with SLE risk genotypes, which increases to over 4-fold after stimulation. Similar analyses of fifteen other SLE risk loci identified 1206 functional variants tightly linked with disease-associated SNPs and demonstrated that common disease alleles contain multiple causal variants modulating multiple immune system genes.

Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases

Complex and dynamic networks of molecules are involved in human diseases. High-throughput technologies enable omics studies interrogating thousands to millions of makers with similar biochemical properties (eg, transcriptomics for RNA transcripts). However, a single layer of "omics" can only provide limited insights into the biological mechanisms of a disease. In the case of genome-wide association studies, although thousands of single nucleotide polymorphisms have been identified for complex diseases and traits, the functional implications and mechanisms of the associated loci are largely unknown. Additionally, the genomic variants alone are not able to explain the changing disease risk across the life span. DNA, RNA, protein, and metabolite often have complementary roles to jointly perform a certain biological function. Such complementary effects and synergistic interactions between omic layers in the life course can only be captured by integrative study of multiple molecular layers. Building upon the success in single-omics discovery research, population studies started adopting the multi-omics approach to better understanding the molecular function and disease etiology. Multi-omics approaches integrate data obtained from different omic levels to understand their interrelation and combined influence on the disease processes. Here, we summarize major omics approaches available in population research, and review integrative approaches and methodologies interrogating multiple omic layers, which enhance the gene discovery and functional analysis of human diseases. We seek to provide analytical recommendations for different types of multi-omics data and study designs to guide the emerging multi-omic research, and to suggest improvement of the existing analytical methods.

Fast and efficient QTL mapper for thousands of molecular phenotypes

Motivation: In order to discover quantitative trait loci, multi-dimensional genomic datasets combining DNA-seq and ChiP-/RNA-seq require methods that rapidly correlate tens of thousands of molecular phenotypes with millions of genetic variants while appropriately controlling for multiple testing.

Results: We have developed FastQTL, a method that implements a popular cis-QTL mapping strategy in a user- and cluster-friendly tool. FastQTL also proposes an efficient permutation procedure to control for multiple testing. The outcome of permutations is modeled using beta distributions trained from a few permutations and from which adjusted P-values can be estimated at any level of significance with little computational cost. The Geuvadis & GTEx pilot datasets can be now easily analyzed an order of magnitude faster than previous approaches.

Availability and implementation: Source code, binaries and comprehensive documentation of FastQTL are freely available to download at http://fastqtl.sourceforge.net/

Contact:emmanouil.dermitzakis@unige.ch or olivier.delaneau@unige.ch

Supplementary information: Supplementary data are available at Bioinformatics online.

The Genotype and Phenotype (GaP) registry: a living biobank for the analysis of quantitative traits

We describe the development of the Genotype and Phenotype (GaP) Registry, a living biobank of normal volunteers who are genotyped for genetic markers related to human disease. Participants in the GaP can be recalled for hypothesis driven study of disease associated genetic variants. The GaP has facilitated functional studies of several autoimmune disease associated loci including Csk, Blk, PDRM1 (Blimp-1) and PTPN22. It is likely that expansion of such living biobank registries will play an important role in studying and understanding the function of disease associated alleles in complex disease.

Genetic association analyses implicate aberrant regulation of innate and adaptive immunity genes in the pathogenesis of systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is a genetically complex autoimmune disease characterized by loss of immune tolerance to nuclear and cell surface antigens. Previous genome-wide association studies (GWAS) had modest sample sizes, reducing their scope and reliability. Our study comprised 7,219 cases and 15,991 controls of European ancestry, constituting a new GWAS, a meta-analysis with a published GWAS and a replication study. We have mapped 43 susceptibility loci, including ten new associations. Assisted by dense genome coverage, imputation provided evidence for missense variants underpinning associations in eight genes. Other likely causal genes were established by examining associated alleles for cis-acting eQTL effects in a range of ex vivo immune cells. We found an over-representation (n = 16) of transcription factors among SLE susceptibility genes. This finding supports the view that aberrantly regulated gene expression networks in multiple cell types in both the innate and adaptive immune response contribute to the risk of developing SLE.

Intrahaplotypic Variants Differentiate Complex Linkage Disequilibrium within Human MHC Haplotypes

Distinct regions of long-range genetic fixation in the human MHC region, known as conserved extended haplotypes (CEHs), possess unique genomic characteristics and are strongly associated with numerous diseases. While CEHs appear to be homogeneous by SNP analysis, the nature of fine variations within their genomic structure is unknown. Using multiple, MHC-homozygous cell lines, we demonstrate extensive sequence conservation in two common Asian MHC haplotypes: A33-B58-DR3 and A2-B46-DR9. However, characterization of phase-resolved MHC haplotypes revealed unique intra-CEH patterns of variation and uncovered 127 single nucleotide variants (SNVs) which are missing from public databases. We further show that the strong linkage disequilibrium structure within the human MHC that typically confounds precise identification of genetic features can be resolved using intra-CEH variants, as evidenced by rs3129063 and rs448489, which affect expression of ZFP57, a gene important in methylation and epigenetic regulation. This study demonstrates an improved strategy that can be used towards genetic dissection of diseases.

Genetic risk factors for decreased bone mineral accretion in children with asthma receiving multiple oral corticosteroid bursts

BACKGROUND

Long-term intermittent oral corticosteroid (OCS) use in children with asthma leads to significant decreases in bone mineral accretion (BMA).

OBJECTIVE

We aimed to identify genetic factors influencing OCS dose effects on BMA in children with asthma.

METHODS

We first performed a gene-by-OCS interaction genome-wide association study (GWAS) of BMA in 489 white participants in the Childhood Asthma Management Program trial who took short-term oral prednisone bursts when they experienced acute asthma exacerbations. We selected the top-ranked 2000 single nucleotide polymorphisms (SNPs) in the GWAS and determined whether these SNPs also had cis-regulatory effects on dexamethasone-induced gene expression in osteoblasts.

RESULTS

We identified 2 SNPs (rs9896933 and rs2074439) associated with decreased BMA and related to the tubulin γ pathway. The rs9896933 variant met the criteria for genome-wide significance (P = 3.15 × 10(-8) in the GWAS) and is located on the intron of tubulin folding cofactor D (TBCD) gene. The rs2074439 variant (P = 2.74 × 10(-4) in the GWAS) showed strong cis-regulatory effects on dexamethasone-induced tubulin γ gene expression in osteoblasts (P = 8.64 × 10(-4)). Interestingly, we found that BMA worsened with increasing prednisone dose as the number of mutant alleles of the 2 SNPs increased.

CONCLUSIONS

We have identified 2 novel tubulin γ pathway SNPs, rs9896933 and rs2074439, showing independent interactive effects with cumulative corticosteroid dose on BMA in children with asthma receiving multiple OCS bursts.

MT-HESS: an efficient Bayesian approach for simultaneous association detection in OMICS datasets, with application to eQTL mapping in multiple tissues

MOTIVATION

Analysing the joint association between a large set of responses and predictors is a fundamental statistical task in integrative genomics, exemplified by numerous expression Quantitative Trait Loci (eQTL) studies. Of particular interest are the so-called ': hotspots ': , important genetic variants that regulate the expression of many genes. Recently, attention has focussed on whether eQTLs are common to several tissues, cell-types or, more generally, conditions or whether they are specific to a particular condition.

RESULTS

We have implemented MT-HESS, a Bayesian hierarchical model that analyses the association between a large set of predictors, e.g. SNPs, and many responses, e.g. gene expression, in multiple tissues, cells or conditions. Our Bayesian sparse regression algorithm goes beyond ': one-at-a-time ': association tests between SNPs and responses and uses a fully multivariate model search across all linear combinations of SNPs, coupled with a model of the correlation between condition/tissue-specific responses. In addition, we use a hierarchical structure to leverage shared information across different genes, thus improving the detection of hotspots. We show the increase of power resulting from our new approach in an extensive simulation study. Our analysis of two case studies highlights new hotspots that would remain undetected by standard approaches and shows how greater prediction power can be achieved when several tissues are jointly considered.

AVAILABILITY AND IMPLEMENTATION

C[Formula: see text] source code and documentation including compilation instructions are available under GNU licence at http://www.mrc-bsu.cam.ac.uk/software/.