Common genetic variants modulate pathogen-sensing responses in human dendritic cells

Writ large: Genomic dissection of the effect of cellular environment on immune response

Cells of the immune system routinely respond to cues from their local environment and feed back to their surroundings through transient responses, choice of differentiation trajectories, plastic changes in cell state, and malleable adaptation to their tissue of residence. Genomic approaches have opened the way for comprehensive interrogation of such orchestrated responses. Focusing on genomic profiling of transcriptional and epigenetic cell states, we discuss how they are applied to investigate immune cells faced with various environmental cues. We highlight some of the emerging principles on the role of dense regulatory circuitry, epigenetic memory, cell type fluidity, and reuse of regulatory modules in achieving and maintaining appropriate responses to a changing environment. These provide a first step toward a systematic understanding of molecular circuits in complex tissues.

Differential Aging Analysis in Human Cerebral Cortex Identifies Variants in TMEM106B and GRN that Regulate Aging Phenotypes

Human age-associated traits, such as cognitive decline, can be highly variable across the population, with some individuals exhibiting traits that are not expected at a given chronological age. Here we present differential aging (Δ-aging), an unbiased method that quantifies individual variability in age-associated phenotypes within a tissue of interest, and apply this approach to the analysis of existing transcriptome-wide cerebral cortex gene expression data from several cohorts totaling 1,904 autopsied human brain samples. We subsequently performed a genome-wide association study and identified the TMEM106B and GRN gene loci, previously associated with frontotemporal dementia, as determinants of Δ-aging in the cerebral cortex with genome-wide significance. TMEM106B risk variants are associated with inflammation, neuronal loss, and cognitive deficits, even in the absence of known brain disease, and their impact is highly selective for the frontal cerebral cortex of older individuals (>65 years). The methodological framework we describe can be broadly applied to the analysis of quantitative traits associated with aging or with other parameters.

Maintenance of macrophage transcriptional programs and intestinal homeostasis by epigenetic reader SP140

Epigenetic "readers" that recognize defined posttranslational modifications on histones have become desirable therapeutic targets for cancer and inflammation. SP140 is one such bromodomain- and plant homeodomain (PHD)-containing reader with immune-restricted expression, and single-nucleotide polymorphisms (SNPs) within SP140 associate with Crohn's disease (CD). However, the function of SP140 and the consequences of disease-associated SP140 SNPs have remained unclear. We show that SP140 is critical for transcriptional programs that uphold the macrophage state. SP140 preferentially occupies promoters of silenced, lineage-inappropriate genes bearing the histone modification H3K27me3, such as the HOXA cluster in human macrophages, and ensures their repression. Depletion of SP140 in mouse or human macrophages resulted in severely compromised microbe-induced activation. We reveal that peripheral blood mononuclear cells (PBMCs) or B cells from individuals carrying CD-associated SNPs within SP140 have defective SP140 messenger RNA splicing and diminished SP140 protein levels. Moreover, CD patients carrying SP140 SNPs displayed suppressed innate immune gene signatures in a mixed population of PBMCs that stratified them from other CD patients. Hematopoietic-specific knockdown of Sp140 in mice resulted in exacerbated dextran sulfate sodium (DSS)-induced colitis, and low SP140 levels in human CD intestinal biopsies correlated with relatively lower intestinal innate cytokine levels and improved response to anti-tumor necrosis factor (TNF) therapy. Thus, the epigenetic reader SP140 is a key regulator of macrophage transcriptional programs for cellular state, and a loss of SP140 due to genetic variation contributes to a molecularly defined subset of CD characterized by ineffective innate immunity, normally critical for intestinal homeostasis.

Genomics of Islet (Dys)function and Type 2 Diabetes

Pancreatic islet dysfunction and beta cell failure are hallmarks of type 2 diabetes mellitus (T2DM) pathogenesis. In this review, we discuss how genome-wide association studies (GWASs) and recent developments in islet (epi)genome and transcriptome profiling (particularly single cell analyses) are providing novel insights into the genetic, environmental, and cellular contributions to islet (dys)function and T2DM pathogenesis. Moving forward, study designs that interrogate and model genetic variation [e.g., allelic profiling and (epi)genome editing] will be critical to dissect the molecular genetics of T2DM pathogenesis, to build next-generation cellular and animal models, and to develop precision medicine approaches to detect, treat, and prevent islet (dys)function and T2DM.

Confounding effects of microbiome on the susceptibility of TNFSF15 to Crohn's disease in the Ryukyu Islands

Crohn's disease (CD) involves chronic inflammation in the gastrointestinal tract due to dysregulation of the host immune response to the gut microbiome. Even though the host-microbiome interactions are likely contributors to the development of CD, a few studies have detected genetic variants that change bacterial compositions and increase CD risk. We focus on one of the well-replicated susceptible genes, tumor necrosis factor superfamily member 15 (TNFSF15), and apply statistical analyses for personal profiles of genotypes and salivary microbiota collected from CD cases and controls in the Ryukyu Islands, southernmost islands of the Japanese archipelago. Our association test confirmed the susceptibility of TNFSF15 in the Ryukyu Islands. We found that the recessive model was supported to fit the observed genotype frequency of risk alleles slightly better than the additive model, defining the genetic effect on CD if a pair of the chromosomes in an individual consists of all risk alleles. The combined analysis of haplotypes and salivary microbiome from a small set of samples showed a significant association of the genetic effect with the increase of Prevotella, which led to a significant increase of CD risk. However, the genetic effect on CD disappeared if the abundance of Prevotella was low, suggesting the genetic contribution to CD is conditionally independent given a fixed amount of Prevotella. Although our statistical power is limited due to the small sample size, these results support an idea that the genetic susceptibility of TNFSF15 to CD may be confounded, in part, by the increase of Prevotella.

Making Mouse Models That Reflect Human Immune Responses

Humans are infected with a variety of acute and chronic pathogens over the course of their lives, and pathogen-driven selection has shaped the immune system of humans. The same is likely true for mice. However, laboratory mice we use for most biomedical studies are bred in ultra-hygienic environments, and are kept free of specific pathogens. We review recent studies that indicate that pathogen infections are important for the basal level of activation and the function of the immune system. Consideration of these environmental exposures of both humans and mice can potentially improve mouse models of human disease.

Global variation in gene expression and the value of diverse sampling

The genomics era has accelerated our understanding of how genetic and epigenetic factors influence both normal variable traits and disease risk in humans. However, the majority of "omics" studies have focused on individuals living in urban centers, primarily from Europe and Asia, neglecting much of the genetic and environmental variation that exists across worldwide populations. Comparative studies of gene regulation in ethnically diverse populations are informing our understanding of how evolutionary forces have shaped the genetic and molecular mechanisms underlying complex traits, and studying gene expression in different environmental contexts is enabling the dissection of disease-related pathways such as immune response. Such approaches are vital to the equitable application of genomics and medicine.

Genome-wide association study of primary sclerosing cholangitis identifies new risk loci and quantifies the genetic relationship with inflammatory bowel disease

Primary sclerosing cholangitis (PSC) is a rare progressive disorder leading to bile duct destruction; ∼75% of patients have comorbid inflammatory bowel disease (IBD). We undertook the largest genome-wide association study of PSC (4,796 cases and 19,955 population controls) and identified four new genome-wide significant loci. The most associated SNP at one locus affects splicing and expression of UBASH3A, with the protective allele (C) predicted to cause nonstop-mediated mRNA decay and lower expression of UBASH3A. Further analyses based on common variants suggested that the genome-wide genetic correlation (r_G) between PSC and ulcerative colitis (UC) (r_G = 0.29) was significantly greater than that between PSC and Crohn's disease (CD) (r_G = 0.04) (P = 2.55 × 10^-15). UC and CD were genetically more similar to each other (r_G = 0.56) than either was to PSC (P < 1.0 × 10^-15). Our study represents a substantial advance in understanding of the genetics of PSC.

Immunogenetic Pathogenesis of Celiac Disease and Non-celiac Gluten Sensitivity

Celiac disease is the most common oral intolerance in Western countries. It results from an immune response towards gluten proteins from certain cereals in genetically predisposed individuals (HLA-DQ2 and/or HLA-DQ8). Its pathogenesis involves the adaptive (HLA molecules, transglutaminase 2, dendritic cells, and CD4(+) T-cells) and the innate immunity with an IL-15-mediated response elicited in the intraepithelial compartment. At present, the only treatment is a permanent strict gluten-free diet (GFD). Multidisciplinary studies have provided a deeper insight of the genetic and immunological factors and their interaction with the microbiota in the pathogenesis of the disease. Similarly, a better understanding of the composition of the toxic gluten peptides has improved the ways to detect them in food and drinks and how to monitor GFD compliance via non-invasive approaches. This review, therefore, addresses the major findings obtained in the last few years including the re-discovery of non-celiac gluten sensitivity.

Non-Coding Loss-of-Function Variation in Human Genomes

Whole-genome and exome sequencing in human populations has revealed the tolerance of each gene for loss-of-function variation. By understanding this tolerance, it has become increasingly possible to identify genes that would make safe therapeutic targets and to identify rare genetic risk factors and phenotypes at the scale of individual genomes. To date, the vast majority of surveyed loss-of-function variants are in protein-coding regions of the genome mainly due to the focus on these regions by exome-based sequencing projects and their relative ease of interpretability. As whole-genome sequencing becomes more prevalent, new strategies will be required to uncover impactful variation in non-coding regions of the genome where the architecture of genome function is more complex. In this review, we investigate recent studies of loss-of-function variation and emerging approaches for interpreting whole-genome sequencing data to identify rare and impactful non-coding loss-of-function variants.

Systems Genetics as a Tool to Identify Master Genetic Regulators in Complex Disease

Systems genetics stems from systems biology and similarly employs integrative modeling approaches to describe the perturbations and phenotypic effects observed in a complex system. However, in the case of systems genetics the main source of perturbation is naturally occurring genetic variation, which can be analyzed at the systems-level to explain the observed variation in phenotypic traits. In contrast with conventional single-variant association approaches, the success of systems genetics has been in the identification of gene networks and molecular pathways that underlie complex disease. In addition, systems genetics has proven useful in the discovery of master trans-acting genetic regulators of functional networks and pathways, which in many cases revealed unexpected gene targets for disease. Here we detail the central components of a fully integrated systems genetics approach to complex disease, starting from assessment of genetic and gene expression variation, linking DNA sequence variation to mRNA (expression QTL mapping), gene regulatory network analysis and mapping the genetic control of regulatory networks. By summarizing a few illustrative (and successful) examples, we highlight how different data-modeling strategies can be effectively integrated in a systems genetics study.

Comparison of Two Meta-Analysis Methods: Inverse-Variance-Weighted Average and Weighted Sum of Z-Scores

The meta-analysis has become a widely used tool for many applications in bioinformatics, including genome-wide association studies. A commonly used approach for meta-analysis is the fixed effects model approach, for which there are two popular methods: the inverse variance-weighted average method and weighted sum of z-scores method. Although previous studies have shown that the two methods perform similarly, their characteristics and their relationship have not been thoroughly investigated. In this paper, we investigate the optimal characteristics of the two methods and show the connection between the two methods. We demonstrate that the each method is optimized for a unique goal, which gives us insight into the optimal weights for the weighted sum of z-scores method. We examine the connection between the two methods both analytically and empirically and show that their resulting statistics become equivalent under certain assumptions. Finally, we apply both methods to the Wellcome Trust Case Control Consortium data and demonstrate that the two methods can give distinct results in certain study designs.

Primary immunodeficiencies suggest redundancy within the human immune system

Pathogen-driven evolution has shaped the complexity of the human immune system. Our genome contains at least 1854 gene products involved in immune responses. However, the redundancy and robustness of the immune system need further characterization. One way to examine this redundancy is through the study of monogenic primary immunodeficiencies (PIDs) associated with infections. Causal mutations affecting innate immunity genes are, in relative terms, close to seven times less frequent than those affecting adaptive immunity genes in PIDs. Loss-of-function mutations of innate immunity genes encoding pattern-recognition receptors (PRRs) and associated pathways rarely cause susceptibility to infections, which suggests that PRR pathways are partially redundant in the immune responses to infection. This dispensability has also been observed for constitutive products of the immune system, such as secretory immunoglobulin A, and for innate immune cells, such as natural killer and innate lymphoid cell subsets, which are not essential for viability. This Review discusses these findings in the context of their implications for the identification of previously unknown classes of PIDs and assessment of the susceptibility to infection associated with various targeted immunotherapies.

Genetic Ancestry and Natural Selection Drive Population Differences in Immune Responses to Pathogens

Individuals from different populations vary considerably in their susceptibility to immune-related diseases. To understand how genetic variation and natural selection contribute to these differences, we tested for the effects of African versus European ancestry on the transcriptional response of primary macrophages to live bacterial pathogens. A total of 9.3% of macrophage-expressed genes show ancestry-associated differences in the gene regulatory response to infection, and African ancestry specifically predicts a stronger inflammatory response and reduced intracellular bacterial growth. A large proportion of these differences are under genetic control: for 804 genes, more than 75% of ancestry effects on the immune response can be explained by a single cis- or trans-acting expression quantitative trait locus (eQTL). Finally, we show that genetic effects on the immune response are strongly enriched for recent, population-specific signatures of adaptation. Together, our results demonstrate how historical selective events continue to shape human phenotypic diversity today, including for traits that are key to controlling infection.

Genetic Adaptation and Neandertal Admixture Shaped the Immune System of Human Populations

Humans differ in the outcome that follows exposure to life-threatening pathogens, yet the extent of population differences in immune responses and their genetic and evolutionary determinants remain undefined. Here, we characterized, using RNA sequencing, the transcriptional response of primary monocytes from Africans and Europeans to bacterial and viral stimuli-ligands activating Toll-like receptor pathways (TLR1/2, TLR4, and TLR7/8) and influenza virus-and mapped expression quantitative trait loci (eQTLs). We identify numerous cis-eQTLs that contribute to the marked differences in immune responses detected within and between populations and a strong trans-eQTL hotspot at TLR1 that decreases expression of pro-inflammatory genes in Europeans only. We find that immune-responsive regulatory variants are enriched in population-specific signals of natural selection and show that admixture with Neandertals introduced regulatory variants into European genomes, affecting preferentially responses to viral challenges. Together, our study uncovers evolutionarily important determinants of differences in host immune responsiveness between human populations.

Prior knowledge guided eQTL mapping for identifying candidate genes

Background

Expression quantitative trait loci (eQTL) mapping is often used to identify genetic loci and candidate genes correlated with traits. Although usually a group of genes affect complex traits, genes in most eQTL mapping methods are considered as independent. Recently, some eQTL mapping methods have accounted for correlated genes, used biological prior knowledge and applied these in model species such as yeast or mouse. However, biological prior knowledge might be very limited for most species.

Results

We proposed a data-driven prior knowledge guided eQTL mapping for identifying candidate genes. At first, quantitative trait loci (QTL) analysis was used to identify single nucleotide polymorphisms (SNP) markers that are associated with traits. Then co-expressed gene modules were generated and gene modules significantly associated with traits were selected. Prior knowledge from QTL mapping was used for eQTL mapping on the selected modules. We tested and compared prior knowledge guided eQTL mapping to the eQTL mapping with no prior knowledge in a simulation study and two barley stem rust resistance case studies.

The results in simulation study and real barley case studies show that models using prior knowledge outperform models without prior knowledge. In the first case study, three gene modules were selected and one of the gene modules was enriched with defense response Gene Ontology (GO) terms. Also, one probe in the gene module is mapped to Rpg1, previously identified as resistance gene to stem rust. In the second case study, four gene modules are identified, one gene module is significantly enriched with defense response to fungus and bacterium.

Conclusions

Prior knowledge guided eQTL mapping is an effective method for identifying candidate genes. The case studies in stem rust show that this approach is robust, and outperforms methods with no prior knowledge in identifying candidate genes.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1387-9) contains supplementary material, which is available to authorized users.

Embracing Complexity beyond Systems Medicine: A New Approach to Chronic Immune Disorders

In order to combat chronic immune disorders (CIDs), it is an absolute necessity to understand the bigger picture, one that goes beyond insights at a one-disease, molecular, cellular, and static level. To unravel this bigger picture we advocate an integral, cross-disciplinary approach capable of embracing the complexity of the field. This paper discusses the current knowledge on common pathways in CIDs including general psychosocial and lifestyle factors associated with immune functioning. We demonstrate the lack of more in-depth psychosocial and lifestyle factors in current research cohorts and most importantly the need for an all-encompassing analysis of these factors. The second part of the paper discusses the challenges of understanding immune system dynamics and effectively integrating all key perspectives on immune functioning, including the patient’s perspective itself. This paper suggests the use of techniques from complex systems science in describing and simulating healthy or deviating behavior of the immune system in its biopsychosocial surroundings. The patient’s perspective data are suggested to be generated by using specific narrative techniques. We conclude that to gain more insight into the behavior of the whole system and to acquire new ways of combatting CIDs, we need to construct and apply new techniques in the field of computational and complexity science, to an even wider variety of dynamic data than used in today’s systems medicine.

Identification of context-dependent expression quantitative trait loci in whole blood

Genetic risk factors often localize to noncoding regions of the genome with unknown effects on disease etiology. Expression quantitative trait loci (eQTLs) help to explain the regulatory mechanisms underlying these genetic associations. Knowledge of the context that determines the nature and strength of eQTLs may help identify cell types relevant to pathophysiology and the regulatory networks underlying disease. Here we generated peripheral blood RNA-seq data from 2,116 unrelated individuals and systematically identified context-dependent eQTLs using a hypothesis-free strategy that does not require previous knowledge of the identity of the modifiers. Of the 23,060 significant cis-regulated genes (false discovery rate (FDR) ≤ 0.05), 2,743 (12%) showed context-dependent eQTL effects. The majority of these effects were influenced by cell type composition. A set of 145 cis-eQTLs depended on type I interferon signaling. Others were modulated by specific transcription factors binding to the eQTL SNPs.

Human immune system variation

The human immune system is highly variable between individuals but relatively stable over time within a given person. Recent conceptual and technological advances have enabled systems immunology analyses, which reveal the composition of immune cells and proteins in populations of healthy individuals. The range of variation and some specific influences that shape an individual's immune system is now becoming clearer. Human immune systems vary as a consequence of heritable and non-heritable influences, but symbiotic and pathogenic microbes and other non-heritable influences explain most of this variation. Understanding when and how such influences shape the human immune system is key for defining metrics of immunological health and understanding the risk of immune-mediated and infectious diseases.

variancePartition: interpreting drivers of variation in complex gene expression studies

Background

As large-scale studies of gene expression with multiple sources of biological and technical variation become widely adopted, characterizing these drivers of variation becomes essential to understanding disease biology and regulatory genetics.

Results

We describe a statistical and visualization framework, variancePartition, to prioritize drivers of variation based on a genome-wide summary, and identify genes that deviate from the genome-wide trend. Using a linear mixed model, variancePartition quantifies variation in each expression trait attributable to differences in disease status, sex, cell or tissue type, ancestry, genetic background, experimental stimulus, or technical variables. Analysis of four large-scale transcriptome profiling datasets illustrates that variancePartition recovers striking patterns of biological and technical variation that are reproducible across multiple datasets.

Conclusions

Our open source software, variancePartition, enables rapid interpretation of complex gene expression studies as well as other high-throughput genomics assays. variancePartition is available from Bioconductor: http://bioconductor.org/packages/variancePartition.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1323-z) contains supplementary material, which is available to authorized users.

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.

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.

Structural and functional annotation of human FAM26F: A multifaceted protein having a critical role in the immune system

BACKGROUND

Human immune system is a complex amalgam of a greatly diverse ensemble comprising of various cellular and non-cellular components, including proteins. FAM26F (family with sequence similarity 26, member F) is a relatively recently identified gene reported to play important role in diverse immune responses. Numerous studies have reported FAM26F to be differentially expressed in several viral, bacterial and parasitic infections, in certain pathophysiological conditions such as heart and liver transplantation, and in several cancers. FAM26F has also been found to be upregulated by various stimulants such as polyI:C, LPS, INF gamma and TNF alpha, and via various anticipated pathways including TLR3, TLR4 IFN-β and Dectin-1. Moreover, the synergistic expression of FAM26F on both NK-cells and myeloid dendritic cells is required to activate NK-cells against tumors via its cytoplasmic tail, thus emphasizing the therapeutic potential of FAM26F for NK sensitive tumors. Although a considerable amount of evidence is present regarding the potential role of FAM26F in immune modulation, the exact function and modulatory pathways of this gene are yet to be elucidated. We aimed to completely characterize FAM26F in order to apprehend its function and role in the immune responses.

RESULTS

The results revealed human FAM26F to be located at chromosomal position 6q22.1. FAM26F mRNA contains 1141bp coding region encoding a 315 amino acid long, stable protein that has been well-conserved throughout evolution. It is a signal peptide deprived transmembrane protein that is secreted through non-classical pathway. The presence of a single well-conserved Ca_hom_mod domain indicated FAM26F to be a cation channel involved in the transport of molecules. A potential N-glycosylation and 14 phosphorylation sites were also predicted, along with four interacting partners of FAM26F. The secondary and tertiary structures of FAM26F were determined. Moreover, the presence of an immunoglobulin-like fold in FAM26F emphasized its role in immune responses.

CONCLUSION

This is the first in silico structural and functional characterization of FAM26F which will be helpful in better understanding the role of FAM26F in the context of the immune system and may also lead to the identification of novel therapeutic targets.

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.

Local Adaptation of Sun-Exposure-Dependent Gene Expression Regulation in Human Skin

Sun-exposure is a key environmental variable in the study of human evolution. Several skin-pigmentation genes serve as classical examples of positive selection, suggesting that sun-exposure has significantly shaped worldwide genomic variation. Here we investigate the interaction between genetic variation and sun-exposure, and how this impacts gene expression regulation. Using RNA-Seq data from 607 human skin samples, we identified thousands of transcripts that are differentially expressed between sun-exposed skin and non-sun-exposed skin. We then tested whether genetic variants may influence each individual’s gene expression response to sun-exposure. Our analysis revealed 10 sun-exposure-dependent gene expression quantitative trait loci (se-eQTLs), including genes involved in skin pigmentation (SLC45A2) and epidermal differentiation (RASSF9). The allele frequencies of the RASSF9 se-eQTL across diverse populations correlate with the magnitude of solar radiation experienced by these populations, suggesting local adaptation to varying levels of sunlight. These results provide the first examples of sun-exposure-dependent regulatory variation and suggest that this variation has contributed to recent human adaptation.

Varying levels of sun-exposure across the world have significantly shaped human evolution. Previous analyses have found several skin pigmentation genes with evidence of strong evolutionary pressures throughout human history, manifesting as large differences in the frequency of genomic variants across populations. But even within populations, individuals respond differently to sun-exposure, suggesting variation in addition to the major differences in skin pigmentation across populations. Here we investigated whether genetic variants associate with response to sun-exposure within Europeans. To measure the response we analyzed gene expression in sun-exposed and non-sun-exposed skin, and identified ten genetic variants that associated with the sun-exposure response of nearby genes. One of these genetic variants, which associated with the sun-exposure response of the gene RASSF9, showed evidence of adaptation in humans in response to solar radiation. Together this evidence suggests that the regulation of gene expression is influenced by sun-exposure and that the sun-exposure dependent effect on RASSF9 expression may have had an effect on human fitness. To our knowledge, this is the first example of an environment-dependent regulatory variant with evidence of adaptation in humans.

Pre-infection transcript levels of FAM26F in peripheral blood mononuclear cells inform about overall plasma viral load in acute and post-acute phase after simian immunodeficiency virus infection

CD8⁺ cells from simian immunodeficiency virus (SIV)-infected long-term non-progressors and some uninfected macaques can suppress viral replication in vitro without killing the infected cells. The aim of this study was to identify factors responsible for non-cytolytic viral suppression by transcriptional profiling and to investigate their potential impact on SIV replication. Results of microarray experiments and further validation with cells from infected and uninfected macaques revealed that FAM26F RNA levels distinguished CD8⁺ cells of controllers and non-controllers (P=0.001). However, FAM26F was also expressed in CD4⁺ T-cells and B-cells. FAM26F expression increased in lymphocytes after in vitro IFN-γ treatment on average 40-fold, and ex vivo FAM26F RNA levels in peripheral blood mononuclear cells correlated with plasma IFN-γ but not with IFN-α. Baseline FAM26F expression appeared to be stable for months, albeit the individual expression levels varied up to tenfold. Investigating its role in SIV-infection revealed that FAM26F was upregulated after infection (P<0.0008), but did not directly correlate with viral load in contrast to MX1 and CXCL10. However, pre-infection levels of FAM26F correlated inversely with overall plasma viral load (AUC) during the acute and post-acute phases of infection (e.g. AUC weeks post infection 0–8; no AIDS vaccine: P<0.0001, Spearman rank correlation coefficient (rs)=−0.89, n=16; immunized with an AIDS vaccine: P=0.033, rs=−0.43; n=25). FAM26F transcript levels prior to infection can provide information about the pace and strength of the antiviral immune response during the early stage of infection. FAM26F expression represented, in our experiments, one of the earliest prognostic markers, and could supplement major histocompatibility complex (MHC)-typing to predict disease progression before SIV-infection.

A potential role for genome structure in the translation of mechanical force during immune cell development

Immune cells react to a wide range of environments, both chemical and physical. While the former has been extensively studied, there is growing evidence that physical and in particular mechanical forces also affect immune cell behavior and development. In order to elicit a response that affects immune cell behavior or development, environmental signals must often reach the nucleus. Chemical and mechanical signals can initiate signal transduction pathways, but mechanical forces may also have a more direct route to the nucleus, altering nuclear shape via mechanotransduction. The three-dimensional organization of DNA allows for the possibility that altering nuclear shape directly remodels chromatin, redistributing critical regulatory elements and proteins, and resulting in wide-scale gene expression changes. As such, integrating mechanotransduction and genome architecture into the immunology toolkit will improve our understanding of immune development and disease.

Standardized Whole-Blood Transcriptional Profiling Enables the Deconvolution of Complex Induced Immune Responses

Systems approaches for the study of immune signaling pathways have been traditionally based on purified cells or cultured lines. However, in vivo responses involve the coordinated action of multiple cell types, which interact to establish an inflammatory microenvironment. We employed standardized whole-blood stimulation systems to test the hypothesis that responses to Toll-like receptor ligands or whole microbes can be defined by the transcriptional signatures of key cytokines. We found 44 genes, identified using Support Vector Machine learning, that captured the diversity of complex innate immune responses with improved segregation between distinct stimuli. Furthermore, we used donor variability to identify shared inter-cellular pathways and trace cytokine loops involved in gene expression. This provides strategies for dimension reduction of large datasets and deconvolution of innate immune responses applicable for characterizing immunomodulatory molecules. Moreover, we provide an interactive R-Shiny application with healthy donor reference values for induced inflammatory genes.

Characterisation of the global transcriptional response to heat shock and the impact of individual genetic variation

BACKGROUND

The heat shock transcriptional response is essential to effective cellular function under stress. This is a highly heritable trait but the nature and extent of inter-individual variation in heat shock response remains unresolved.

METHODS

We determined global transcription profiles of the heat shock response for a panel of lymphoblastoid cell lines established from 60 founder individuals in the Yoruba HapMap population. We explore the observed differentially expressed gene sets following heat shock, establishing functional annotations, underlying networks and nodal genes involving heat shock factor 1 recruitment. We define a multivariate phenotype for the global transcriptional response to heat shock using partial least squares regression and map this quantitative trait to associated genetic variation in search of the major genomic modulators.

RESULTS

A comprehensive dataset of differentially expressed genes following heat shock in humans is presented. We identify nodal genes downstream of heat shock factor 1 in this gene set, notably involving ubiquitin C and small ubiquitin-like modifiers together with transcription factors. We dissect a multivariate phenotype for the global heat shock response which reveals distinct clustering of individuals in terms of variance of the heat shock response and involves differential expression of genes involved in DNA replication and cell division in some individuals. We find evidence of genetic associations for this multivariate response phenotype that involves trans effects modulating expression of genes following heat shock, including HSF1 and UBQLN1.

CONCLUSION

This study defines gene expression following heat shock for a cohort of individuals, establishing insights into the biology of the heat shock response and hypotheses for how variation in this may be modulated by underlying genetic diversity.

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.

Alzheimer's disease-associated TREM2 variants exhibit either decreased or increased ligand-dependent activation

INTRODUCTION

TREM2 is a lipid-sensing activating receptor on microglia known to be important for Alzheimer's disease (AD), but whether it plays a beneficial or detrimental role in disease pathogenesis is controversial.

METHODS

We analyzed AD risk of TREM2 variants in the NIMH AD Genetics Initiative Study and AD Sequencing Project. We compared each variant's risk and functional impact by a reporter assay. Finally, we analyzed expression of TREM2 on human monocytes.

RESULTS

We provide more evidence for increased AD risk associated with several TREM2 variants, and show that these variants decreased or markedly increased binding to TREM2 ligands. We identify HDL and LDL as novel TREM2 ligands. We also show that TREM2 expression in human monocytes is minimal compared to monocyte-derived dendritic cells.

DISCUSSION

Our results suggest that TREM2 signaling helps protect against AD but can cause harm in excess, supporting the idea that proper TREM2 function is important to counteract disease progression.

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.

Immunophenotyping of rheumatoid arthritis reveals a linkage between HLA-DRB1 genotype, CXCR4 expression on memory CD4(+) T cells, and disease activity

Rheumatoid arthritis (RA) is a chronic autoimmune inflammatory disease that leads to destructive arthritis. Although the HLA class II locus is the strongest genetic risk factor for rheumatoid arthritis, the relationship between HLA class II alleles and lymphocyte activation remains unclear. We performed immunophenotyping of peripheral blood mononuclear cells on 91 HLA-DRB1-genotyped RA patients and 110 healthy donors. The frequency of memory CXCR4⁺CD4⁺ T cells, and not Th1 and Th17 cells, was significantly associated with disease severity by multiple linear regression analysis. RA patients with one or more susceptible HLA-DR haplotypes (shared epitope: SE) displayed a significantly higher frequency of memory CXCR4⁺CD4⁺ T cells. Moreover, the frequency of memory CXCR4⁺CD4⁺ T cells significantly correlated with the expression level of HLA-DR on B cells, which was elevated in RA patients with SE. In vitro analysis and transcriptomic pathway analysis suggested that the interaction between HLA-DR and T cell receptors is an important regulator of memory CXCR4⁺CD4⁺ T cells. Clinically, a higher frequency of memory CXCR4⁺CD4⁺ T cells predicted a better response to CTLA4-Ig. Memory CXCR4⁺CD4⁺ T cells may serve as a powerful biomarker for unraveling the linkage between HLA-DRB1 genotype and disease activity in RA.

Inter-individual variability and genetic influences on cytokine responses to bacteria and fungi

Little is known about the inter-individual variation of cytokine responses to different pathogens in healthy individuals. To systematically describe cytokine responses elicited by distinct pathogens and to determine the effect of genetic variation on cytokine production, we profiled cytokines produced by peripheral blood mononuclear cells from 197 individuals of European origin from the 200 Functional Genomics (200FG) cohort in the Human Functional Genomics Project (http://www.humanfunctionalgenomics.org), obtained over three different years. We compared bacteria- and fungi-induced cytokine profiles and found that most cytokine responses were organized around a physiological response to specific pathogens, rather than around a particular immune pathway or cytokine. We then correlated genome-wide single-nucleotide polymorphism (SNP) genotypes with cytokine abundance and identified six cytokine quantitative trait loci (QTLs). Among them, a cytokine QTL at the NAA35-GOLM1 locus markedly modulated interleukin (IL)-6 production in response to multiple pathogens and was associated with susceptibility to candidemia. Furthermore, the cytokine QTLs that we identified were enriched among SNPs previously associated with infectious diseases and heart diseases. These data reveal and begin to explain the variability in cytokine production by human immune cells in response to pathogens.

Putting the Genome in Context: Gene-Environment Interactions in Type 2 Diabetes

The genome is often the conduit through which environmental exposures convey their effects on health and disease. Whilst not all diseases act by directly perturbing the genome, the phenotypic responses are often genetically determined. Hence, whilst diseases are often defined has having differing degrees of genetic determination, genetic and environmental factors are, with few exceptions, inseparable features of most diseases, not least type 2 diabetes. It follows that to optimize diabetes, prevention and treatment will require that the etiological roles of genetic and environmental risk factors be jointly considered. As we discuss here, studies focused on quantifying gene-environment and gene-treatment interactions are gathering momentum and may eventually yield data that helps guide health-related choices and medical interventions for type 2 diabetes and other complex diseases.

Parsing the Interferon Transcriptional Network and Its Disease Associations

Type 1 interferon (IFN) is a key mediator of organismal responses to pathogens, eliciting prototypical "interferon signature genes" that encode antiviral and inflammatory mediators. For a global view of IFN signatures and regulatory pathways, we performed gene expression and chromatin analyses of the IFN-induced response across a range of immunocyte lineages. These distinguished ISGs by cell-type specificity, kinetics, and sensitivity to tonic IFN and revealed underlying changes in chromatin configuration. We combined 1,398 human and mouse datasets to computationally infer ISG modules and their regulators, validated by genetic analysis in both species. Some ISGs are controlled by Stat1/2 and Irf9 and the ISRE DNA motif, but others appeared dependent on non-canonical factors. This regulatory framework helped to interpret JAK1 blockade pharmacology, different clusters being affected under tonic or IFN-stimulated conditions, and the IFN signatures previously associated with human diseases, revealing unrecognized subtleties in disease footprints, as affected by human ancestry.

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.

Variants in TRIM22 That Affect NOD2 Signaling Are Associated With Very-Early-Onset Inflammatory Bowel Disease

BACKGROUND & AIMS

Severe forms of inflammatory bowel disease (IBD) that develop in very young children can be caused by variants in a single gene. We performed whole-exome sequence (WES) analysis to identify genetic factors that might cause granulomatous colitis and severe perianal disease, with recurrent bacterial and viral infections, in an infant of consanguineous parents.

METHODS

We performed targeted WES analysis of DNA collected from the patient and her parents. We validated our findings by a similar analysis of DNA from 150 patients with very-early-onset IBD not associated with known genetic factors analyzed in Toronto, Oxford, and Munich. We compared gene expression signatures in inflamed vs noninflamed intestinal and rectal tissues collected from patients with treatment-resistant Crohn's disease who participated in a trial of ustekinumab. We performed functional studies of identified variants in primary cells from patients and cell culture.

RESULTS

We identified a homozygous variant in the tripartite motif containing 22 gene (TRIM22) of the patient, as well as in 2 patients with a disease similar phenotype. Functional studies showed that the variant disrupted the ability of TRIM22 to regulate nucleotide binding oligomerization domain containing 2 (NOD2)-dependent activation of interferon-beta signaling and nuclear factor-κB. Computational studies demonstrated a correlation between the TRIM22-NOD2 network and signaling pathways and genetic factors associated very early onset and adult-onset IBD. TRIM22 is also associated with antiviral and mycobacterial effectors and markers of inflammation, such as fecal calprotectin, C-reactive protein, and Crohn's disease activity index scores.

CONCLUSIONS

In WES and targeted exome sequence analyses of an infant with severe IBD characterized by granulomatous colitis and severe perianal disease, we identified a homozygous variant of TRIM22 that affects the ability of its product to regulate NOD2. Combined computational and functional studies showed that the TRIM22-NOD2 network regulates antiviral and antibacterial signaling pathways that contribute to inflammation. Further study of this network could lead to new disease markers and therapeutic targets for patients with very early and adult-onset IBD.

Integrative genomics analyses unveil downstream biological effectors of disease-specific polymorphisms buried in intergenic regions

Functionally altered biological mechanisms arising from disease-associated polymorphisms, remain difficult to characterise when those variants are intergenic, or, fall between genes. We sought to identify shared downstream mechanisms by which inter- and intragenic single-nucleotide polymorphisms (SNPs) contribute to a specific physiopathology. Using computational modelling of 2 million pairs of disease-associated SNPs drawn from genome-wide association studies (GWAS), integrated with expression Quantitative Trait Loci (eQTL) and Gene Ontology functional annotations, we predicted 3,870 inter–intra and inter–intra SNP pairs with convergent biological mechanisms (FDR<0.05). These prioritised SNP pairs with overlapping messenger RNA targets or similar functional annotations were more likely to be associated with the same disease than unrelated pathologies (OR>12). We additionally confirmed synergistic and antagonistic genetic interactions for a subset of prioritised SNP pairs in independent studies of Alzheimer’s disease (entropy P=0.046), bladder cancer (entropy P=0.039), and rheumatoid arthritis (PheWAS case–control P<10⁻⁴). Using ENCODE data sets, we further statistically validated that the biological mechanisms shared within prioritised SNP pairs are frequently governed by matching transcription factor binding sites and long-range chromatin interactions. These results provide a ‘roadmap’ of disease mechanisms emerging from GWAS and further identify candidate therapeutic targets among downstream effectors of intergenic SNPs.

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.

Cistromic and genetic evidence that the vitamin D receptor mediates susceptibility to latitude-dependent autoimmune diseases

The vitamin D receptor (VDR) is a ligand-activated transcription factor that regulates gene expression in many cell types, including immune cells. It requires binding of 1,25 dihydroxy vitamin D3 (1,25D3) for activation. Many autoimmune diseases show latitude-dependent prevalence and/or association with vitamin D deficiency, and vitamin D supplementation is commonly used in their clinical management. 1,25D3 is regulated by genes associated with the risk of autoimmune diseases and predominantly expressed in myeloid cells. We determined the VDR cistrome in monocytes and monocyte-derived inflammatory (DC1) and tolerogenic dendritic cells (DC2). VDR motifs were highly overrepresented in ChIP-Seq peaks in stimulated monocyte (40%), DC1 (21%) and DC2 (47%), P<E(-100) for all. Of the nearly 11 000 VDR-binding peaks identified across the genome in DC1s, 1317 were shared with DC2s (91% of DC2 sites) and 1579 with monocytes (83% of monocyte sites). Latitude-dependent autoimmune disease risk polymorphisms were highly overrepresented within 5 kb of the peaks. Several transcription factor recognition motifs were highly overrepresented in the peaks, including those for the autoimmune risk gene, BATF. This evidence indicates that VDR regulates hundreds of myeloid cell genes and that the molecular pathways controlled by VDR in these cells are important in maintaining tolerance.

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.

Integrated analyses of gene expression and genetic association studies in a founder population

Genome-wide association studies (GWASs) have become a standard tool for dissecting genetic contributions to disease risk. However, these studies typically require extraordinarily large sample sizes to be adequately powered. Strategies that incorporate functional information alongside genetic associations have proved successful in increasing GWAS power. Following this paradigm, we present the results of 20 different genetic association studies for quantitative traits related to complex diseases, conducted in the Hutterites of South Dakota. To boost the power of these association studies, we collected RNA-sequencing data from lymphoblastoid cell lines for 431 Hutterite individuals. We then used Sherlock, a tool that integrates GWAS and expression quantitative trait locus (eQTL) data, to identify weak GWAS signals that are also supported by eQTL data. Using this approach, we found novel associations with quantitative phenotypes related to cardiovascular disease, including carotid intima-media thickness, left atrial volume index, monocyte count and serum YKL-40 levels.

A block mixture model to map eQTLs for gene clustering and networking

To study how genes function in a cellular and physiological process, a general procedure is to classify gene expression profiles into categories based on their similarity and reconstruct a regulatory network for functional elements. However, this procedure has not been implemented with the genetic mechanisms that underlie the organization of gene clusters and networks, despite much effort made to map expression quantitative trait loci (eQTLs) that affect the expression of individual genes. Here we address this issue by developing a computational approach that integrates gene clustering and network reconstruction with genetic mapping into a unifying framework. The approach can not only identify specific eQTLs that control how genes are clustered and organized toward biological functions, but also enable the investigation of the biological mechanisms that individual eQTLs perturb in a signaling pathway. We applied the new approach to characterize the effects of eQTLs on the structure and organization of gene clusters in Caenorhabditis elegans. This study provides the first characterization, to our knowledge, of the effects of genetic variants on the regulatory network of gene expression. The approach developed can also facilitate the genetic dissection of other dynamic processes, including development, physiology and disease progression in any organisms.