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

What is next after the genes for autoimmunity?

Clinical pathologies draw us to envisage disease as either an independent entity or a diverse set of traits governed by common physiopathological mechanisms, prompted by environmental assaults throughout life. Autoimmune diseases are not an exception, given they represent a diverse collection of diseases in terms of their demographic profile and primary clinical manifestations. Although they are pleiotropic outcomes of non-specific disease genes underlying similar immunogenetic mechanisms, research generally focuses on a single disease. Drastic technologic advances are leading research to organize clinical genomic multidisciplinary approaches to decipher the nature of human biological systems. Once the currently costly omic-based technologies become universally accessible, the way will be paved for a cleaner picture to risk quantification, prevention, prognosis and diagnosis, allowing us to clearly define better phenotypes always ensuring the integrity of the individuals studied. However, making accurate predictions for most autoimmune diseases is an ambitious challenge, since the understanding of these pathologies is far from complete. Herein, some pitfalls and challenges of the genetics of autoimmune diseases are reviewed, and an approximation to the future of research in this field is presented.

Replication and meta-analysis of GWAS identified susceptibility loci in Kawasaki disease confirm the importance of B lymphoid tyrosine kinase (BLK) in disease susceptibility

The BLK and CD40 loci have been associated with Kawasaki disease (KD) in two genome-wide association studies (GWAS) conducted in a Taiwanese population of Han Chinese ancestry (Taiwanese) and in Japanese cohorts. Here we build on these findings with replication studies of the BLK and CD40 loci in populations of Korean and European descent. The BLK region was significantly associated with KD susceptibility in both populations. Within the BLK gene the rs2736340-located linkage disequilibrium (LD ) comprising the promoter and first intron was strongly associated with KD, with the combined results of Asian studies including Taiwanese, Japanese, and Korean populations (2,539 KD patients and 7,021 controls) providing very compelling evidence of association (rs2736340, OR = 1.498, 1.354–1.657; P = 4.74×10⁻³¹). We determined the percentage of B cells present in the peripheral blood mononuclear cell (PBMC) population and the expression of BLK in the peripheral blood leukocytes (leukocytes) of KD patients during the acute and convalescent stages. The percentage of B cells in the PBMC population and the expression of BLK in leukocytes were induced in patients in the acute stage of KD. In B cell lines derived from KD patients, and in purified B cells from KD patients obtained during the acute stage, those with the risk allele of rs2736340 expressed significantly lower levels of BLK. These results suggest that peripheral B cells play a pathogenic role during the acute stage of KD. Decreased BLK expression in peripheral blood B cells may alter B cell function and predispose individuals to KD. These associative data suggest a role for B cells during acute KD. Understanding the functional implications may facilitate the development of B cell-mediated therapy for KD.

SNP association mapping across the extended major histocompatibility complex and risk of B-cell precursor acute lymphoblastic leukemia in children

The extended major histocompatibility complex (xMHC) is the most gene-dense region of the genome and harbors a disproportionately large number of genes involved in immune function. The postulated role of infection in the causation of childhood B-cell precursor acute lymphoblastic leukemia (BCP-ALL) suggests that the xMHC may make an important contribution to the risk of this disease. We conducted association mapping across an approximately 4 megabase region of the xMHC using a validated panel of single nucleotide polymorphisms (SNPs) in childhood BCP-ALL cases (n=567) enrolled in the Northern California Childhood Leukemia Study (NCCLS) compared with population controls (n=892). Logistic regression analyses of 1,145 SNPs, adjusted for age, sex, and Hispanic ethnicity indicated potential associations between several SNPs and childhood BCP-ALL. After accounting for multiple comparisons, one of these included a statistically significant increased risk associated with rs9296068 (OR=1.40, 95% CI=1.19-1.66, corrected p=0.036), located in proximity to HLA-DOA. Sliding window haplotype analysis identified an additional locus located in the extended class I region in proximity to TRIM27 tagged by a haplotype comprising rs1237485, rs3118361, and rs2032502 (corrected global p=0.046). Our findings suggest that susceptibility to childhood BCP-ALL is influenced by genetic variation within the xMHC and indicate at least two important regions for future evaluation.

Next-generation sequencing in understanding complex neurological disease

Next-generation sequencing techniques have made vast quantities of data on human genomes and transcriptomes available to researchers. Huge progress has been made towards understanding the basis of many Mendelian neurological conditions, but progress has been considerably slower in complex neurological diseases (multiple sclerosis, migraine, Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and so on). The authors review current next-generation sequencing methodologies and present selected studies illustrating how these have been used to cast light on the genetic etiology of complex neurological diseases with specific focus on multiple sclerosis. The authors highlight particular pitfalls in next-generation sequencing experiments and speculate on both clinical and research applications of these sequencing platforms for complex neurological disorders in the future.

Genetic insights into common pathways and complex relationships among immune-mediated diseases

Shared aetiopathogenic factors among immune-mediated diseases have long been suggested by their co-familiality and co-occurrence, and molecular support has been provided by analysis of human leukocyte antigen (HLA) haplotypes and genome-wide association studies. The interrelationships can now be better appreciated following the genotyping of large immune disease sample sets on a shared SNP array: the 'Immunochip'. Here, we systematically analyse loci shared among major immune-mediated diseases. This reveals that several diseases share multiple susceptibility loci, but there are many nuances. The most associated variant at a given locus frequently differs and, even when shared, the same allele often has opposite associations. Interestingly, risk alleles conferring the largest effect sizes are usually disease-specific. These factors help to explain why early evidence of extensive 'sharing' is not always reflected in epidemiological overlap.

Integrative modeling of eQTLs and cis-regulatory elements suggests mechanisms underlying cell type specificity of eQTLs

Genetic variants in cis-regulatory elements or trans-acting regulators frequently influence the quantity and spatiotemporal distribution of gene transcription. Recent interest in expression quantitative trait locus (eQTL) mapping has paralleled the adoption of genome-wide association studies (GWAS) for the analysis of complex traits and disease in humans. Under the hypothesis that many GWAS associations tag non-coding SNPs with small effects, and that these SNPs exert phenotypic control by modifying gene expression, it has become common to interpret GWAS associations using eQTL data. To fully exploit the mechanistic interpretability of eQTL-GWAS comparisons, an improved understanding of the genetic architecture and causal mechanisms of cell type specificity of eQTLs is required. We address this need by performing an eQTL analysis in three parts: first we identified eQTLs from eleven studies on seven cell types; then we integrated eQTL data with cis-regulatory element (CRE) data from the ENCODE project; finally we built a set of classifiers to predict the cell type specificity of eQTLs. The cell type specificity of eQTLs is associated with eQTL SNP overlap with hundreds of cell type specific CRE classes, including enhancer, promoter, and repressive chromatin marks, regions of open chromatin, and many classes of DNA binding proteins. These associations provide insight into the molecular mechanisms generating the cell type specificity of eQTLs and the mode of regulation of corresponding eQTLs. Using a random forest classifier with cell specific CRE-SNP overlap as features, we demonstrate the feasibility of predicting the cell type specificity of eQTLs. We then demonstrate that CREs from a trait-associated cell type can be used to annotate GWAS associations in the absence of eQTL data for that cell type. We anticipate that such integrative, predictive modeling of cell specificity will improve our ability to understand the mechanistic basis of human complex phenotypic variation.

When interpreting genome-wide association studies showing that specific genetic variants are associated with disease risk, scientists look for a link between the genetic variant and a biological mechanism behind that disease. One functional mechanism is that the genetic variant may influence gene transcription via a co-localized genomic regulatory element, such as a transcription factor binding site within an open chromatin region. Often this type of regulation occurs in some cell types but not others. In this study, we look across eleven gene expression studies with seven cell types and consider how genetic transcription regulators, or eQTLs, replicate within and between cell types. We identify pervasive allelic heterogeneity, or transcriptional control of a single gene by multiple, independent eQTLs. We integrate extensive data on cell type specific regulatory elements from ENCODE to identify general methods of transcription regulation through enrichment of eQTLs within regulatory elements. We also build a classifier to predict eQTL replication across cell types. The results in this paper present a path to an integrative, predictive approach to improve our ability to understand the mechanistic basis of human phenotypic variation.

Refining susceptibility loci of chronic obstructive pulmonary disease with lung eqtls

Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of mortality worldwide. Recent genome-wide association studies (GWAS) have identified robust susceptibility loci associated with COPD. However, the mechanisms mediating the risk conferred by these loci remain to be found. The goal of this study was to identify causal genes/variants within susceptibility loci associated with COPD. In the discovery cohort, genome-wide gene expression profiles of 500 non-tumor lung specimens were obtained from patients undergoing lung surgery. Blood-DNA from the same patients were genotyped for 1,2 million SNPs. Following genotyping and gene expression quality control filters, 409 samples were analyzed. Lung expression quantitative trait loci (eQTLs) were identified and overlaid onto three COPD susceptibility loci derived from GWAS; 4q31 (HHIP), 4q22 (FAM13A), and 19q13 (RAB4B, EGLN2, MIA, CYP2A6). Significant eQTLs were replicated in two independent datasets (n = 363 and 339). SNPs previously associated with COPD and lung function on 4q31 (rs1828591, rs13118928) were associated with the mRNA expression of HHIP. An association between mRNA expression level of FAM13A and SNP rs2045517 was detected at 4q22, but did not reach statistical significance. At 19q13, significant eQTLs were detected with EGLN2. In summary, this study supports HHIP, FAM13A, and EGLN2 as the most likely causal COPD genes on 4q31, 4q22, and 19q13, respectively. Strong lung eQTL SNPs identified in this study will need to be tested for association with COPD in case-control studies. Further functional studies will also be needed to understand the role of genes regulated by disease-related variants in COPD.

Validating therapeutic targets through human genetics

More than 90% of the compounds that enter clinical trials fail to demonstrate sufficient safety and efficacy to gain regulatory approval. Most of this failure is due to the limited predictive value of preclinical models of disease, and our continued ignorance regarding the consequences of perturbing specific targets over long periods of time in humans. 'Experiments of nature' - naturally occurring mutations in humans that affect the activity of a particular protein target or targets - can be used to estimate the probable efficacy and toxicity of a drug targeting such proteins, as well as to establish causal rather than reactive relationships between targets and outcomes. Here, we describe the concept of dose-response curves derived from experiments of nature, with an emphasis on human genetics as a valuable tool to prioritize molecular targets in drug development. We discuss empirical examples of drug-gene pairs that support the role of human genetics in testing therapeutic hypotheses at the stage of target validation, provide objective criteria to prioritize genetic findings for future drug discovery efforts and highlight the limitations of a target validation approach that is anchored in human genetics.

Major histocompatibility complex genomics and human disease

Over several decades, various forms of genomic analysis of the human major histocompatibility complex (MHC) have been extremely successful in picking up many disease associations. This is to be expected, as the MHC region is one of the most gene-dense and polymorphic stretches of human DNA. It also encodes proteins critical to immunity, including several controlling antigen processing and presentation. Single-nucleotide polymorphism genotyping and human leukocyte antigen (HLA) imputation now permit the screening of large sample sets, a technique further facilitated by high-throughput sequencing. These methods promise to yield more precise contributions of MHC variants to disease. However, interpretation of MHC-disease associations in terms of the functions of variants has been problematic. Most studies confirm the paramount importance of class I and class II molecules, which are key to resistance to infection. Infection is likely driving the extreme variation of these genes across the human population, but this has been difficult to demonstrate. In contrast, many associations with autoimmune conditions have been shown to be specific to certain class I and class II alleles. Interestingly, conditions other than infections and autoimmunity are also associated with the MHC, including some cancers and neuropathies. These associations could be indirect, owing, for example, to the infectious history of a particular individual and selective pressures operating at the population level.

Insights into TREM2 biology by network analysis of human brain gene expression data

Rare variants in TREM2 cause susceptibility to late-onset Alzheimer's disease. Here we use microarray-based expression data generated from 101 neuropathologically normal individuals and covering 10 brain regions, including the hippocampus, to understand TREM2 biology in human brain. Using network analysis, we detect a highly preserved TREM2-containing module in human brain, show that it relates to microglia, and demonstrate that TREM2 is a hub gene in 5 brain regions, including the hippocampus, suggesting that it can drive module function. Using enrichment analysis we show significant overrepresentation of genes implicated in the adaptive and innate immune system. Inspection of genes with the highest connectivity to TREM2 suggests that it plays a key role in mediating changes in the microglial cytoskeleton necessary not only for phagocytosis, but also migration. Most importantly, we show that the TREM2-containing module is significantly enriched for genes genetically implicated in Alzheimer's disease, multiple sclerosis, and motor neuron disease, implying that these diseases share common pathways centered on microglia and that among the genes identified are possible new disease-relevant genes.

The potential use of expression profiling: implications for predicting treatment response in rheumatoid arthritis

Whole genome expression profiling, or transcriptomics, is a high throughput technology with the potential for major impacts in both clinical settings and drug discovery and diagnostics. In particular, there is much interest in this technique as a mechanism for predicting treatment response. Gene expression profiling entails the quantitative measurement of messenger RNA levels for thousands of genes simultaneously with the inherent possibility of identifying biomarkers of response to a particular therapy or by singling out those at risk of serious adverse events. This technology should contribute to the era of stratified medicine, in which patient specific populations are matched to potentially beneficial drugs via clinical tests. Indeed, in the oncology field, gene expression testing is already recommended to allow rational use of therapies to treat breast cancer. However, there are still many issues surrounding the use of the various testing platforms available and the statistical analysis associated with the interpretation of results generated. This review will discuss the implications this promising technology has in predicting treatment response and outline the various advantages and pitfalls associated with its use.

Meta-analysis of genome-wide association studies identifies ten loci influencing allergic sensitization

Allergen-specific immunoglobulin E (present in allergic sensitization) has a central role in the pathogenesis of allergic disease. We performed the first large-scale genome-wide association study (GWAS) of allergic sensitization in 5,789 affected individuals and 10,056 controls and followed up the top SNP at each of 26 loci in 6,114 affected individuals and 9,920 controls. We increased the number of susceptibility loci with genome-wide significant association with allergic sensitization from three to ten, including SNPs in or near TLR6, C11orf30, STAT6, SLC25A46, HLA-DQB1, IL1RL1, LPP, MYC, IL2 and HLA-B. All the top SNPs were associated with allergic symptoms in an independent study. Risk-associated variants at these ten loci were estimated to account for at least 25% of allergic sensitization and allergic rhinitis. Understanding the molecular mechanisms underlying these associations may provide new insights into the etiology of allergic disease.

Systems biological approaches to measure and understand vaccine immunity in humans

Recent studies have demonstrated the utility of using systems approaches to identify molecular signatures that can be used to predict vaccine immunity in humans. Such approaches are now being used extensively in vaccinology, and are beginning to yield novel insights about the molecular networks driving vaccine immunity. In this review, we present a broad review of the methodologies involved in these studies, and discuss the promise and challenges involved in this emerging field of "systems vaccinology."

A genetic screen identifies interferon-α effector genes required to suppress hepatitis C virus replication

BACKGROUND & AIMS

Hepatitis C virus (HCV) infection is a leading cause of end-stage liver disease. Interferon-α (IFNα) is an important component of anti-HCV therapy; it up-regulates transcription of IFN-stimulated genes, many of which have been investigated for their antiviral effects. However, all of the genes required for the antiviral function of IFNα (IFN effector genes [IEGs]) are not known. IEGs include not only IFN-stimulated genes, but other nontranscriptionally induced genes that are required for the antiviral effect of IFNα. In contrast to candidate approaches based on analyses of messenger RNA (mRNA) expression, identification of IEGs requires a broad functional approach.

METHODS

We performed an unbiased genome-wide small interfering RNA screen to identify IEGs that inhibit HCV. Huh7.5.1 hepatoma cells were transfected with small interfering RNAs incubated with IFNα and then infected with JFH1 HCV. Cells were stained using HCV core antibody, imaged, and analyzed to determine the percent infection. Candidate IEGs detected in the screen were validated and analyzed further.

RESULTS

The screen identified 120 previously unreported IEGs. From these, we more fully evaluated the following: asparagine-linked glycosylation 10 homolog (yeast, α-1,2-glucosyltransferase); butyrylcholinesterase; dipeptidyl-peptidase 4 (CD26, adenosine deaminase complexing protein 2); glucokinase (hexokinase 4) regulator; guanylate cyclase 1, soluble, β 3; MYST histone acetyltransferase 1; protein phosphatase 3 (formerly 2B), catalytic subunit, β isoform; peroxisomal proliferator-activated receptor-γ-DBD-interacting protein 1; and solute carrier family 27 (fatty acid transporter), member 2; and demonstrated that they enabled IFNα-mediated suppression of HCV at multiple steps of its life cycle. Expression of these genes had more potent effects against flaviviridae because a subset was required for IFNα to suppress dengue virus but not influenza A virus. In addition, many of the host genes detected in this screen (92%) were not transcriptionally stimulated by IFNα; these genes represent a heretofore unknown class of non-IFN-stimulated gene IEGs.

CONCLUSIONS

We performed a whole-genome loss-of-function screen to identify genes that mediate the effects of IFNα against human pathogenic viruses. We found that IFNα restricts HCV via actions of general and specific IEGs.

Exploiting gene expression variation to capture gene-environment interactions for disease

Gene-environment interactions have long been recognized as a fundamental concept in evolutionary, quantitative, and medical genetics. In the genomics era, study of how environment and genome interact to shape gene expression variation is relevant to understanding the genetic architecture of complex phenotypes. While genetic analysis of gene expression variation focused on main effects, little is known about the extent of interaction effects implicating regulatory variants and their consequences on transcriptional variation. Here we survey the current state of the concept of transcriptional gene-environment interactions and discuss its utility for mapping disease phenotypes in light of the insights gained from genome-wide association studies of gene expression.

Global properties and functional complexity of human gene regulatory variation

Identification and functional interpretation of gene regulatory variants is a major focus of modern genomics. The application of genetic mapping to molecular and cellular traits has enabled the detection of regulatory variation on genome-wide scales and revealed an enormous diversity of regulatory architecture in humans and other species. In this review I summarise the insights gained and questions raised by a decade of genetic mapping of gene expression variation. I discuss recent extensions of this approach using alternative molecular phenotypes that have revealed some of the biological mechanisms that drive gene expression variation between individuals. Finally, I highlight outstanding problems and future directions for development.

Human genetics in rheumatoid arthritis guides a high-throughput drug screen of the CD40 signaling pathway

Although genetic and non-genetic studies in mouse and human implicate the CD40 pathway in rheumatoid arthritis (RA), there are no approved drugs that inhibit CD40 signaling for clinical care in RA or any other disease. Here, we sought to understand the biological consequences of a CD40 risk variant in RA discovered by a previous genome-wide association study (GWAS) and to perform a high-throughput drug screen for modulators of CD40 signaling based on human genetic findings. First, we fine-map the CD40 risk locus in 7,222 seropositive RA patients and 15,870 controls, together with deep sequencing of CD40 coding exons in 500 RA cases and 650 controls, to identify a single SNP that explains the entire signal of association (rs4810485, P = 1.4×10⁻⁹). Second, we demonstrate that subjects homozygous for the RA risk allele have ∼33% more CD40 on the surface of primary human CD19+ B lymphocytes than subjects homozygous for the non-risk allele (P = 10⁻⁹), a finding corroborated by expression quantitative trait loci (eQTL) analysis in peripheral blood mononuclear cells from 1,469 healthy control individuals. Third, we use retroviral shRNA infection to perturb the amount of CD40 on the surface of a human B lymphocyte cell line (BL2) and observe a direct correlation between amount of CD40 protein and phosphorylation of RelA (p65), a subunit of the NF-κB transcription factor. Finally, we develop a high-throughput NF-κB luciferase reporter assay in BL2 cells activated with trimerized CD40 ligand (tCD40L) and conduct an HTS of 1,982 chemical compounds and FDA–approved drugs. After a series of counter-screens and testing in primary human CD19+ B cells, we identify 2 novel chemical inhibitors not previously implicated in inflammation or CD40-mediated NF-κB signaling. Our study demonstrates proof-of-concept that human genetics can be used to guide the development of phenotype-based, high-throughput small-molecule screens to identify potential novel therapies in complex traits such as RA.

A current challenge in human genetics is to follow-up “hits” from genome-wide association studies (GWAS) to guide drug discovery for complex traits. Previously, we identified a common variant in the CD40 locus as associated with risk of rheumatoid arthritis (RA). Here, we fine-map the CD40 signal of association through a combination of dense genotyping and exonic sequencing in large patient collections. Further, we demonstrate that the RA risk allele is a gain-of-function allele that increases the amount of CD40 on the surface of primary human B lymphocyte cells from healthy control individuals. Based on these observations, we develop a high-throughput assay to recapitulate the biology of the RA risk allele in a system suitable for a small molecule drug screen. After a series of primary screens and counter screens, we identify small molecules that inhibit CD40-mediated NF-kB signaling in human B cells. While this is only the first step towards a more comprehensive effort to identify CD40-specific inhibitors that may be used to treat RA, our study demonstrates a successful strategy to progress from a GWAS to a drug screen for complex traits such as RA.

Persistently active microbial molecules prolong innate immune tolerance in vivo

Measures that bolster the resolution phase of infectious diseases may offer new opportunities for improving outcome. Here we show that inactivation of microbial lipopolysaccharides (LPS) can be required for animals to recover from the innate immune tolerance that follows exposure to Gram-negative bacteria. When wildtype mice are exposed to small parenteral doses of LPS or Gram-negative bacteria, their macrophages become reprogrammed (tolerant) for a few days before they resume normal function. Mice that are unable to inactivate LPS, in contrast, remain tolerant for several months; during this time they respond sluggishly to Gram-negative bacterial challenge, with high mortality. We show here that prolonged macrophage reprogramming is maintained in vivo by the persistence of stimulatory LPS molecules within the cells' in vivo environment, where naïve cells can acquire LPS via cell-cell contact or from the extracellular fluid. The findings provide strong evidence that inactivation of a stimulatory microbial molecule can be required for animals to regain immune homeostasis following parenteral exposure to bacteria. Measures that disable microbial molecules might enhance resolution of tissue inflammation and help restore innate defenses in individuals recovering from many different infectious diseases.

We showed previously that mice lacking acyloxyacyl hydrolase (AOAH), the host enzyme that inactivates Gram-negative bacterial lipopolysaccharides (LPS), are unable to regain normal immune responsiveness for many weeks/months after they are exposed in vivo to a small amount of LPS or Gram-negative bacteria. The many possible explanations for slow recovery included long-lasting epigenetic changes in macrophages or other host cells, chronically stimulated cells that produce certain mediators, and persistent signaling by internalized LPS within macrophages. Using several in vivo techniques to study peritoneal macrophages, we found that none of these mechanisms was correct. Rather, prolonged recovery is caused by intact LPS that remains in the environment where macrophages live and can pass from one cell to another in vivo. This is the first evidence that the persistence of a bioactive microbial agonist, per se, can prevent resolution of inflammation in vivo. It also identifies the stimulatory microbial molecule as a realistic target for intervention – in further support, we found that providing recombinant AOAH can be partially preventive. In a larger sense, showing that chemical inactivation of one important microbial signaling molecule is required for full recovery should encourage efforts to find out whether disabling other microbial agonists (chitin, lipopeptides, flagella, others) also benefits infected animals.

Interferon-beta induces distinct gene expression response patterns in human monocytes versus T cells

Background

Monocytes, which are key players in innate immunity, are outnumbered by neutrophils and lymphocytes among peripheral white blood cells. The cytokine interferon-β (IFN-β) is widely used as an immunomodulatory drug for multiple sclerosis and its functional pathways in peripheral blood mononuclear cells (PBMCs) have been previously described. The aim of the present study was to identify novel, cell-specific IFN-β functions and pathways in tumor necrosis factor (TNF)-α-activated monocytes that may have been missed in studies using PBMCs.

Methodology/Principal Findings

Whole genome gene expression profiles of human monocytes and T cells were compared following in vitro priming to TNF-α and overnight exposure to IFN-β. Statistical analyses of the gene expression data revealed a cell-type-specific change of 699 transcripts, 667 monocyte-specific transcripts, 21 T cell-specific transcripts and 11 transcripts with either a difference in the response direction or a difference in the magnitude of response. RT-PCR revealed a set of differentially expressed genes (DEGs), exhibiting responses to IFN-β that are modulated by TNF-α in monocytes, such as RIPK2 and CD83, but not in T cells or PBMCs. Known IFN-β promoter response elements, such as ISRE, were enriched in T cell DEGs but not in monocyte DEGs. The overall directionality of the gene expression regulation by IFN-β was different in T cells and monocytes, with up-regulation more prevalent in T cells, and a similar extent of up and down-regulation recorded in monocytes.

Conclusions

By focusing on the response of distinct cell types and by evaluating the combined effects of two cytokines with pro and anti-inflammatory activities, we were able to present two new findings First, new IFN-β response pathways and genes, some of which were monocytes specific; second, a cell-specific modulation of the IFN-β response transcriptome by TNF-α.

Genetic regulation of human adipose microRNA expression and its consequences for metabolic traits

The genetics of messenger RNA (mRNA) expression has been extensively studied in humans and other organisms, but little is known about genetic factors contributing to microRNA (miRNA) expression. We examined natural variation of miRNA expression in adipose tissue in a population of 200 men who have been carefully characterized for metabolic syndrome (MetSyn) phenotypes as part of the Metabolic Syndrome in Men (METSIM) study. We genotyped the subjects using high-density single-nucleotide polymorphism microarrays and quantified the mRNA abundance using genome-wide expression arrays and miRNA abundance using next-generation sequencing. We reliably quantified 356 miRNA species that were expressed in human adipose tissue, a limited number of which made up most of the expressed miRNAs. We mapped the miRNA abundance as an expression quantitative trait and determined cis regulation of expression for nine of the miRNAs and of the processing of one miRNA (miR-28). The degree of genetic variation of miRNA expression was substantially less than that of mRNAs. For the majority of the miRNAs, genetic regulation of expression was independent of the expression of mRNA from which the miRNA is transcribed. We also showed that for 108 miRNAs, mapped reads displayed widespread variation from the canonical sequence. We found a total of 24 miRNAs to be significantly associated with MetSyn traits. We suggest a regulatory role for miR-204-5p which was predicted to inhibit acetyl coenzyme A carboxylase β, a key fatty acid oxidation enzyme that has been shown to play a role in regulating body fat and insulin resistance in adipose tissue.

Deciphering molecular circuits from genetic variation underlying transcriptional responsiveness to stimuli

Individual genetic variation affects gene responsiveness to stimuli, often by influencing complex molecular circuits. Here we combine genomic and intermediate-scale transcriptional profiling with computational methods to identify variants that affect the responsiveness of genes to stimuli (responsiveness quantitative trait loci or reQTLs) and to position these variants in molecular circuit diagrams. We apply this approach to study variation in transcriptional responsiveness to pathogen components in dendritic cells from recombinant inbred mouse strains. We identify reQTLs that correlate with particular stimuli and position them in known pathways. For example, in response to a virus-like stimulus, a trans-acting variant responds as an activator of the antiviral response; using RNA interference, we identify Rgs16 as the likely causal gene. Our approach charts an experimental and analytic path to decipher the mechanisms underlying genetic variation in circuits that control responses to stimuli.

Gene expression drives local adaptation in humans

The molecular basis of adaptation--and, in particular, the relative roles of protein-coding versus gene expression changes--has long been the subject of speculation and debate. Recently, the genotyping of diverse human populations has led to the identification of many putative "local adaptations" that differ between populations. Here I show that these local adaptations are over 10-fold more likely to affect gene expression than amino acid sequence. In addition, a novel framework for identifying polygenic local adaptations detects recent positive selection on the expression levels of genes involved in UV radiation response, immune cell proliferation, and diabetes-related pathways. These results provide the first examples of polygenic gene expression adaptation in humans, as well as the first genome-scale support for the hypothesis that changes in gene expression have driven human adaptation.

Genome-wide association study in BRCA1 mutation carriers identifies novel loci associated with breast and ovarian cancer risk

BRCA1-associated breast and ovarian cancer risks can be modified by common genetic variants. To identify further cancer risk-modifying loci, we performed a multi-stage GWAS of 11,705 BRCA1 carriers (of whom 5,920 were diagnosed with breast and 1,839 were diagnosed with ovarian cancer), with a further replication in an additional sample of 2,646 BRCA1 carriers. We identified a novel breast cancer risk modifier locus at 1q32 for BRCA1 carriers (rs2290854, P = 2.7 × 10(-8), HR = 1.14, 95% CI: 1.09-1.20). In addition, we identified two novel ovarian cancer risk modifier loci: 17q21.31 (rs17631303, P = 1.4 × 10(-8), HR = 1.27, 95% CI: 1.17-1.38) and 4q32.3 (rs4691139, P = 3.4 × 10(-8), HR = 1.20, 95% CI: 1.17-1.38). The 4q32.3 locus was not associated with ovarian cancer risk in the general population or BRCA2 carriers, suggesting a BRCA1-specific association. The 17q21.31 locus was also associated with ovarian cancer risk in 8,211 BRCA2 carriers (P = 2×10(-4)). These loci may lead to an improved understanding of the etiology of breast and ovarian tumors in BRCA1 carriers. Based on the joint distribution of the known BRCA1 breast cancer risk-modifying loci, we estimated that the breast cancer lifetime risks for the 5% of BRCA1 carriers at lowest risk are 28%-50% compared to 81%-100% for the 5% at highest risk. Similarly, based on the known ovarian cancer risk-modifying loci, the 5% of BRCA1 carriers at lowest risk have an estimated lifetime risk of developing ovarian cancer of 28% or lower, whereas the 5% at highest risk will have a risk of 63% or higher. Such differences in risk may have important implications for risk prediction and clinical management for BRCA1 carriers.

Allelic expression analysis of the osteoarthritis susceptibility gene COL11A1 in human joint tissues

Background

The single nucleotide polymorphism (SNP) rs2615977 is associated with osteoarthritis (OA) and is located in intron 31 of COL11A1, a strong candidate gene for this degenerative musculoskeletal disease. Furthermore, the common non-synonymous COL11A1 SNP rs1676486 is associated with another degenerative musculoskeletal disease, lumbar disc herniation (LDH). rs1676486 is a C-T transition mediating its affect on LDH susceptibility by modulating COL11A1 expression. The risk T-allele of rs1676486 leads to reduced expression of the COL11A1 transcript, a phenomenon known as allelic expression imbalance (AEI). We were keen therefore to assess whether the effect that rs1676486 has on COL11A1 expression in LDH is also observed in OA and whether the rs2615977 association to OA also marked AEI.

Methods

Using RNA from OA cartilage, we assessed whether either SNP correlated with COL11A1 AEI by 1) measuring COL11A1 expression and stratifying the data by genotype at each SNP; and 2) quantifying the mRNA transcribed from each allele of the two SNPs. We also assessed whether rs1676486 was associated with OA susceptibility using a case–control cohort of over 18,000 individuals.

Results

We observed significant AEI at rs1676486 (p < 0.0001) with the T-allele correlating with reduced COL11A1 expression. This corresponded with observations in LDH but the SNP was not associated with OA. We did not observe AEI at rs2615977.

Conclusions

COL11A1 is subject to AEI in OA cartilage. AEI at rs1676486 is a risk factor for LDH, but not for OA. These two diseases therefore share a common functional phenotype, namely AEI of COL11A1, but this appears to be a disease risk only in LDH. Other functional effects on COL11A1 presumably account for the OA susceptibility that maps to this gene.

A refined study of FCRL genes from a genome-wide association study for Graves' disease

To pinpoint the exact location of the etiological variant/s present at 1q21.1 harboring FCRL1-5 and CD5L genes, we carried out a refined association study in the entire FCRL region in 1,536 patients with Graves' disease (GD) and 1,516 sex-matched controls by imputation analysis, logistic regression, and cis-eQTL analysis. Among 516 SNPs with P<0.05 in the initial GWAS scan, the strongest signals associated with GD and correlated to FCRL3 expression were located at a cluster of SNPs including rs7528684 and rs3761959. And the allele-specific effects for rs3761959 and rs7528684 on FCRL3 expression level revealed that the risk alleles A of rs3761959 and C of rs7528684 were correlated with the elevated expression level of FCRL3 whether in PBMCs or its subsets, especially in CD19(+) B cells and CD8(+) T subsets. Next, the combined analysis with 5,300 GD cases and 4,916 control individuals confirmed FCRL3 was a susceptibility gene of GD in Chinese Han populations, and rs3761959 and rs7528684 met the genome-wide association significance level (P(combined) = 2.27×10(-12) and 7.11×10(-13), respectively). Moreover, the haplotypes with the risk allele A of rs3761959 and risk allele C of rs7528684 were associated with GD risk. Finally, our epigenetic analysis suggested the disease-associated C allele of rs7528684 increased affinity for NF-KB transcription factor. Above data indicated that FCRL3 gene and its proxy SNP rs7528684 may be involved in the pathogenesis of GD by excessive inhibiting B cell receptor signaling and the impairment of suppressing function of Tregs.

Molecular network of chromatin immunoprecipitation followed by deep sequencing-based vitamin D receptor target genes

BACKGROUND

Vitamin D is a liposoluble vitamin essential for calcium metabolism. The ligand-bound vitamin D receptor (VDR), heterodimerized with retinoid X receptor, interacts with vitamin D response elements (VDREs) to regulate gene expression. Vitamin D deficiency due to insufficient sunlight exposure confers an increased risk for multiple sclerosis (MS).

OBJECTIVE

To study a protective role of vitamin D in multiple sclerosis (MS), it is important to characterize the global molecular network of VDR target genes (VDRTGs) in immune cells.

METHODS

We identified genome-wide VDRTGs collectively from two distinct chromatin immunoprecipitation followed by deep sequencing (ChIP-Seq) datasets of VDR-binding sites derived from calcitriol-treated human cells of B cell and monocyte origins. We mapped short reads of next generation sequencing (NGS) data on hg19 with Bowtie, detected the peaks with Model-based Analysis of ChIP-Seq (MACS), and identified genomic locations by GenomeJack, a novel genome viewer for NGS platforms.

RESULTS

We found 2997 stringent peaks distributed on protein-coding genes, chiefly located in the promoter and the intron on VDRE DR3 sequences. However, the corresponding transcriptome data verified calcitriol-induced upregulation of only a small set of VDRTGs. The molecular network of 1541 calcitriol-responsive VDRTGs showed a significant relationship with leukocyte transendothelial migration, Fcγ receptor-mediated phagocytosis, and transcriptional regulation by VDR, suggesting a pivotal role of genome-wide VDRTGs in immune regulation.

CONCLUSION

These results suggest the working hypothesis that persistent deficiency of vitamin D might perturb the complex network of VDRTGs in immune cells, being responsible for induction of an autoimmune response causative for MS.

Genomic modulators of the immune response

Our understanding of immunity has historically been informed by studying heritable mutations in both the adaptive and innate immune responses, including primary immunodeficiency and autoimmune diseases. Recent advances achieved through the application of genomic and epigenomic approaches are reshaping the study of immune dysfunction and opening up new avenues for therapeutic interventions. Moreover, applying genomic techniques to resolve functionally important genetic variation between individuals is providing new insights into immune function in health. This review describes progress in the study of rare variants and primary immunodeficiency diseases arising from whole-exome sequencing (WES), and discusses the application, success, and challenges of applying genome-wide association studies (GWAS) to disorders of immune function and how they may inform more rational use of therapeutics. In addition, the application of expression quantitative-trait mapping to immune phenotypes, progress in understanding MHC disease associations, and insights into epigenetic mechanisms at the interface of immunity and the environment are reviewed.

Identification of single nucleotide polymorphisms regulating peripheral blood mRNA expression with genome-wide significance: an eQTL study in the Japanese population

Several recent studies have reported that expression quantitative trait loci (eQTLs) may affect gene expression in a cell-dependent manner. In the current study, a genome-wide eQTL analysis was performed in whole blood samples collected from 76 Japanese subjects. RNA microarray analysis was performed for 3 independent sample groups that were genotyped in a genome-wide scan. The correlations between the genotypes of 534,404 autosomal single nucleotide polymorphisms (SNPs) and the expression levels of 30,465 probes were examined for each sample group. The SNP-probe pairs with combined correlation coefficients of all 3 sample groups corresponding to P<3.1×10⁻¹² (i.e., Bonferroni-corrected P<0.05) were considered significant. SNP-probe pairs with a high likelihood of cross-hybridization and SNP-in-probe effects were excluded to avoid false positive results. We identified 102 cis-acting and 5 trans-acting eQTL regions. The cis-eQTL regions were widely distributed both upstream and downstream of the gene, as well as within the gene. The eQTL SNPs identified were examined for their influence on the expression levels in lymphoblastoid cell lines by using a public database. The results showed that genetic variants affecting expression levels in whole blood may have different effects on gene expression in lymphoblastoid cell lines. Further studies are required to clarify how SNPs function in affecting the expression levels in whole blood as well as in other tissues.

Gene-centric meta-analyses of 108 912 individuals confirm known body mass index loci and reveal three novel signals

Recent genetic association studies have made progress in uncovering components of the genetic architecture of the body mass index (BMI). We used the ITMAT-Broad-Candidate Gene Association Resource (CARe) (IBC) array comprising up to 49 320 single nucleotide polymorphisms (SNPs) across ~2100 metabolic and cardiovascular-related loci to genotype up to 108 912 individuals of European ancestry (EA), African-Americans, Hispanics and East Asians, from 46 studies, to provide additional insight into SNPs underpinning BMI. We used a five-phase study design: Phase I focused on meta-analysis of EA studies providing individual level genotype data; Phase II performed a replication of cohorts providing summary level EA data; Phase III meta-analyzed results from the first two phases; associated SNPs from Phase III were used for replication in Phase IV; finally in Phase V, a multi-ethnic meta-analysis of all samples from four ethnicities was performed. At an array-wide significance (P < 2.40E-06), we identify novel BMI associations in loci translocase of outer mitochondrial membrane 40 homolog (yeast) - apolipoprotein E - apolipoprotein C-I (TOMM40-APOE-APOC1) (rs2075650, P = 2.95E-10), sterol regulatory element binding transcription factor 2 (SREBF2, rs5996074, P = 9.43E-07) and neurotrophic tyrosine kinase, receptor, type 2 [NTRK2, a brain-derived neurotrophic factor (BDNF) receptor gene, rs1211166, P = 1.04E-06] in the Phase IV meta-analysis. Of 10 loci with previous evidence for BMI association represented on the IBC array, eight were replicated, with the remaining two showing nominal significance. Conditional analyses revealed two independent BMI-associated signals in BDNF and melanocortin 4 receptor (MC4R) regions. Of the 11 array-wide significant SNPs, three are associated with gene expression levels in both primary B-cells and monocytes; with rs4788099 in SH2B adaptor protein 1 (SH2B1) notably being associated with the expression of multiple genes in cis. These multi-ethnic meta-analyses expand our knowledge of BMI genetics.

Chromatin marks identify critical cell types for fine mapping complex trait variants

If trait-associated variants alter regulatory regions, then they should fall within chromatin marks in relevant cell types. However, it is unclear which of the many marks are most useful in defining cell types associated with disease and fine mapping variants. We hypothesized that informative marks are phenotypically cell type specific; that is, SNPs associated with the same trait likely overlap marks in the same cell type. We examined 15 chromatin marks and found that those highlighting active gene regulation were phenotypically cell type specific. Trimethylation of histone H3 at lysine 4 (H3K4me3) was the most phenotypically cell type specific (P < 1 × 10(-6)), driven by colocalization of variants and marks rather than gene proximity (P < 0.001). H3K4me3 peaks overlapped with 37 SNPs for plasma low-density lipoprotein concentration in the liver (P < 7 × 10(-5)), 31 SNPs for rheumatoid arthritis within CD4(+) regulatory T cells (P = 1 × 10(-4)), 67 SNPs for type 2 diabetes in pancreatic islet cells (P = 0.003) and the liver (P = 0.003), and 14 SNPs for neuropsychiatric disease in neuronal tissues (P = 0.007). We show how cell type-specific H3K4me3 peaks can inform the fine mapping of associated SNPs to identify causal variation.

Genetics of ANCA-associated vasculitis in Japan: a role for HLA-DRB1*09:01 haplotype

The epidemiology of antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is considerably different between European and Asian populations. Whereas granulomatosis with polyangiitis is the most common form of AAV in northern European populations, microscopic polyangiitis (MPA) accounts for the majority of AAV in Japan. This difference may at least in part derive from the difference in genetic background. In this review, I focus on our observation on HLA, an obvious candidate gene for immune disorders, and discuss its potential implication. In Japanese AAV, significant association was detected with HLA-DRB1*09:01, the carrier frequency of which was increased in MPA [P=0.0087, odds ratio (OR) 1.90, 95% confidence interval (CI) 1.17-3.08] and in myeloperoxidase (MPO)-ANCA-positive AAV (P=0.0016, OR 2.05, 95% CI 1.31-3.23) when compared with healthy Japanese controls. HLA-DRB1*09:01 is one of the most common HLA-DRB1 alleles in Asians but is rare in Caucasian populations. Interestingly, HLA-DRB1*09:01 has been shown to be associated with multiple autoimmune diseases, including type 1 diabetes, rheumatoid arthritis, and systemic lupus erythematosus, suggesting that either HLA-DRB1*09:01 itself or other genes in tight linkage disequilibrium may play a role in a molecular pathway shared by various autoimmune diseases in Japanese and possibly in other Asian populations.

Interrogating the major histocompatibility complex with high-throughput genomics

The major histocompatibility complex (MHC) region on the short arm of chromosome 6 harbors the largest number of replicated associations across the human genome for a wide range of diseases, but the functional basis for these associations is still poorly understood. One fundamental challenge in fine-mapping associations to functional alleles is the enormous sequence diversity and broad linkage disequilibrium of the MHC, both of which hamper the cost-effective interrogation in large patient samples and the identification of causal variants. In this review, we argue that there is now a valuable opportunity to leverage existing genome-wide association study (GWAS) datasets for in-depth investigation to identify independent effects in the MHC. Application of imputation to GWAS data facilitates comprehensive interrogation of the classical human leukocyte antigen (HLA) loci. These datasets are, in many cases, sufficiently large to give investigators the ability to disentangle effects at different loci. We also explain how querying variation at individual amino acid positions for association can be powerful and expand traditional analyses that focus only on the classical HLA types.

Coordinating GWAS results with gene expression in a systems immunologic paradigm in autoimmunity

There has been considerable progress in our understanding of the genetic architecture of susceptibility to inflammatory diseases in recent years: several hundred susceptibility loci have been discovered in genome-wide association studies (GWAS) of human populations. This success has created an important challenge in identifying the functional consequences of these risk-associated variants and in elucidating how the repercussions of individual susceptibility loci integrate to yield dysregulation of immune pathways and, ultimately, syndromic clinical phenotypes. The integration of GWAS association signals with high-resolution transcriptome and other genomic data that capture the dynamics of cellular state and function in the context of individual's collection of susceptibility alleles has proven to be a successful avenue of investigation. The rapid pace of methodological development in this area has been coupled with an accumulation of experimental data that makes the elucidation of complex biological networks underlying susceptibility to these common inflammatory diseases a reasonable goal in the near future.

Anti-inflammatory therapy in type 1 diabetes

Type 1 diabetes (T1D) is a multi-factorial, organ-specific autoimmune disease in genetically susceptible individuals, which is characterized by a selective and progressive loss of insulin-producing β-cells. Cells mediating innate as well as adaptive immunity infiltrate pancreatic islets, thereby generating an aberrant inflammatory process called insulitis that can be mirrored by a pathologic autoantibody production and autoreactive T-cells. In tight cooperation with infiltrating innate immune cells, which secrete high levels of pro-inflammatory cytokines like IL-1β, TNFα, and INFγ effector T-cells trigger the fatal destruction process of β-cells. There is ongoing discussion on the contribution of inflammation in T1D pathogenesis, ranging from a bystander reaction of autoimmunity to a dysregulation of immune responses that initiate inflammatory processes and thereby actively promoting β-cell death. Here, we review recent advances in anti-inflammatory interventions in T1D animal models and preclinical studies and discuss their mode of action as well as their capacity to interfere with T1D development.

Markers of endogenous desaturase activity and risk of coronary heart disease in the CAREMA cohort study

Background

Intakes of n-3 polyunsaturated fatty acids (PUFAs), especially EPA (C20∶5n-3) and DHA (C22∶6n-3), are known to prevent fatal coronary heart disease (CHD). The effects of n-6 PUFAs including arachidonic acid (C20∶4n-6), however, remain unclear. δ-5 and δ-6 desaturases are rate-limiting enzymes for synthesizing long-chain n-3 and n-6 PUFAs. C20∶4n-6 to C20∶3n-6 and C18∶3n-6 to C18∶2n-6 ratios are markers of endogenous δ-5 and δ-6 desaturase activities, but have never been studied in relation to incident CHD. Therefore, the aim of this study was to investigate the relation between these ratios as well as genotypes of FADS1 rs174547 and CHD incidence.

Methods

We applied a case-cohort design within the CAREMA cohort, a large prospective study among the general Dutch population followed up for a median of 12.1 years. Fatty acid profile in plasma cholesteryl esters and FADS1 genotype at baseline were measured in a random subcohort (n = 1323) and incident CHD cases (n = 537). Main outcome measures were hazard ratios (HRs) of incident CHD adjusted for major CHD risk factors.

Results

The AA genotype of rs174547 was associated with increased plasma levels of C204n-6, C20∶5n-3 and C22∶6n-3 and increased δ-5 and δ-6 desaturase activities, but not with CHD risk. In multivariable adjusted models, high baseline δ-5 desaturase activity was associated with reduced CHD risk (P for trend = 0.02), especially among those carrying the high desaturase activity genotype (AA): HR (95% CI) = 0.35 (0.15–0.81) for comparing the extreme quintiles. High plasma DHA levels were also associated with reduced CHD risk.

Conclusion

In this prospective cohort study, we observed a reduced CHD risk with an increased C20∶4n-6 to C20∶3n-6 ratio, suggesting that δ-5 desaturase activity plays a role in CHD etiology. This should be investigated further in other independent studies.

Cell type-specific eQTLs in the human immune system

A new study reports the mapping of gene expression in primary immune cell subsets, showing the presence of cell type-specific cis and trans expression quantitative trait loci (eQTLs). The identification of cell type-specific trans-regulated networks can inform functional studies of susceptibility loci identified from genome-wide association studies for human complex diseases.