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

Genetic and evolutionary determinants of human population variation in immune responses

Humans display remarkable immune response variation when exposed to identical immune challenges. However, our understanding of the genetic, evolutionary, and environmental factors that impact this inter-individual and inter-population immune response heterogeneity is still in its early days. In this review, we discuss three fundamental questions concerning the recent evolution of the human immune system: the degree to which individuals from different populations vary in their innate immune responses, the genetic variants accounting for such differences, and the evolutionary mechanisms that led to the establishment of these variants in modern human populations. We also discuss how past selective events might have contributed to the uneven distribution of immune-related disorders across populations.

The causes and consequences of variation in human cytokine production in health

Cytokines are important cell-signaling molecules that activate and modulate immune responses. Major factors influencing cytokine variation in healthy individuals are host genetics, non-heritable factors and the microbiome. Genetic variation accounts for a significant part of heterogeneity in cytokine production by peripheral blood mononuclear cells. Variation in cytokines such as IL-6 and IL-6Ra is strongly influenced by heritability, suggesting an evolutionarily pressure for their genetic regulation that potentially contributes to differences in immune responsiveness between human populations. Non-heritable factors, including age, body weight and environmental variables such as seasonality, drive variation in baseline cytokine levels. Age further affects pathogen-induced lymphocyte-derived cytokine responses, whereas seasonality affects monocyte-derived cytokine production in response to influenza virus, Coxiella burnetti or Cryptococcus neoformans. Another influential factor that shapes the immune system is the human microbiome. Microbes and microbial products (e.g. short-chain fatty acids and tryptophan metabolites) possess strong immunomodulatory effects, induce regulatory T cells and lead to the diversification of B cells and the production of specific antibodies. In particular, differential TNFα and IFNγ production is associated with the gut microbiome. Understanding causes of variation in the healthy human immune system can reveal factors that lead to aberrant cytokine production in immune-related disorders.

Viewpoint: Toward the Genetic Architecture of Disease Severity in Inflammatory Bowel Diseases

Inflammatory bowel disease (IBD) is characterized by uneven disease courses with various clinical outcomes. A few prognostic markers of disease severity may help stratify patients and identify those who will benefit the most from early aggressive treatment. The concept of disease severity remains too broad and vague, mainly because the definition must embrace several disease mechanisms, mainly inflammation and fibrosis, with various rates of disease progression. The magnitude of inflammation is an obvious key driver of disease severity in IBD that ultimately influence disease behavior. Advances in the genetics underlying disease severity are currently emerging, but attempts to overlap the genetics of disease susceptibility and severity have until now been unsatisfactory, suggesting that the genetic architecture of disease severity may be distinct from the genetics of disease susceptibility. In this review, we report on the current knowledge on disease severity and on the main research venues to decipher the genetic architecture of disease severity.

Early developmental and allometric patterns in the electric yellow cichlid Labidochromis caeruleus

The electric yellow cichlid Labidochromis caeruleus is a mouth-brooding haplochromine cichlid from Lake Malawi and one of the most popular cichlids in the ornamental fish industry. To investigate the early development of L. caeruleus from hatching until the juvenile stage, we studied its morphological development and allometric growth patterns. In newly-hatched larvae, most organs and body parts were not yet differentiated and continued to develop until 15 days post hatching (dph). The yolk sac was depleted at 13 dph. There was allometric growth, primarily in the anterior and posterior regions of the body, and inflection points when trajectories of allometric growth changed. Head and tail growth was prioritized, suggesting that body parts linked to feeding and swimming behaviour mature earlier than the rest of the body. Additionally, growth patterns revealed that development of organs related to vital functions such as branchial respiration, sensation, exogenous feeding and swimming was prioritized. Comparisons with other African and Neotropical cichlids revealed differences in ontogenetic processes and allometric growth along the anterior-posterior axis as well as variation in developmental timing. These results indicate how early morphological development and ontogenic processes might respond to the distinctive parental care observed in mouth-brooding cichlids.

Integration of multi-omics data and deep phenotyping enables prediction of cytokine responses

The immune response to pathogens varies substantially among people. While both genetic and non-genetic factors contribute to inter-person variation, their relative contributions and potential predictive power have remained largely unknown. By systematically correlating host factors in 534 healthy volunteers, including baseline immunological parameters and molecular profiles (genome, metabolome and gut microbiome), with cytokine-production capacity after stimulation with 20 pathogens, we identified distinct patterns of co-regulation. Among the 91 different cytokine–stimulus pairs, 11 categories of host factors together explained up to 67% of inter-individual variation in cytokine production induced by stimulation. A computational model based on genetic data predicted the genetic component of stimulus-induced cytokine-production (correlation 0.28-0.89), while non-genetic factors influenced cytokine production as well.

Lethal Influenza in Two Related Adults with Inherited GATA2 Deficiency

The pathogenesis of life-threatening influenza A virus (IAV) disease remains elusive, as infection is benign in most individuals. We studied two relatives who died from influenza. We Sanger sequenced GATA2 and evaluated the mutation by gene transfer, measured serum cytokine levels, and analyzed circulating T- and B-cells. Both patients (father and son, P1 and P2) died in 2011 of H1N1pdm IAV infection at the ages of 54 and 31 years, respectively. They had not suffered from severe or moderately severe infections in the last 17 (P1) and 15 years (P2). A daughter of P1 had died at 20 years from infectious complications. Low B-cell, NK- cell, and monocyte numbers and myelodysplastic syndrome led to sequence GATA2. Patients were heterozygous for a novel, hypomorphic, R396L mutation leading to haplo-insufficiency. B- and T-cell rearrangement in peripheral blood from P1 during the influenza episode showed expansion of one major clone. No T-cell receptor excision circles were detected in P1 and P3 since they were 35 and 18 years, respectively. Both patients presented an exuberant, interferon (IFN)-γ-mediated hypercytokinemia during H1N1pdm infection. No data about patients with viremia was available. Two previously reported adult GATA2-deficient patients died from severe H1N1 IAV infection; GATA2 deficiency may predispose to life-threatening influenza in adulthood. However, a role of other genetic variants involved in immune responses cannot be ruled out. Patients with GATA2 deficiency can reach young adulthood without severe infections, including influenza, despite long-lasting complete B-cell and natural killer (NK) cell deficiency, as well as profoundly diminished T-cell thymic output.

Interactions between genetic variation and cellular environment in skeletal muscle gene expression

From whole organisms to individual cells, responses to environmental conditions are influenced by genetic makeup, where the effect of genetic variation on a trait depends on the environmental context. RNA-sequencing quantifies gene expression as a molecular trait, and is capable of capturing both genetic and environmental effects. In this study, we explore opportunities of using allele-specific expression (ASE) to discover cis-acting genotype-environment interactions (GxE)—genetic effects on gene expression that depend on an environmental condition. Treating 17 common, clinical traits as approximations of the cellular environment of 267 skeletal muscle biopsies, we identify 10 candidate environmental response expression quantitative trait loci (reQTLs) across 6 traits (12 unique gene-environment trait pairs; 10% FDR per trait) including sex, systolic blood pressure, and low-density lipoprotein cholesterol. Although using ASE is in principle a promising approach to detect GxE effects, replication of such signals can be challenging as validation requires harmonization of environmental traits across cohorts and a sufficient sampling of heterozygotes for a transcribed SNP. Comprehensive discovery and replication will require large human transcriptome datasets, or the integration of multiple transcribed SNPs, coupled with standardized clinical phenotyping.

Diverse mechanisms of IRF5 action in inflammatory responses

Interferon regulatory factor 5 (IRF5) is a key signal-dependent transcription factor in myeloid cells. Its expression is induced by granulocyte-macrophage colony stimulating factor and interferon-gamma. IRF5 protein is further activated in response to stimulation, translocating to the nucleus where it mediates inflammatory responses. IRF5 is capable of both the up-regulation of pro-inflammatory genes and repressing anti-inflammatory mediators, thus polarising macrophages to a pro-inflammatory phenotype. We discuss IRF5 interactions with a wide range of transcriptional regulators that give rise to its diverse effects at the level of chromatin.

Genomic Effects of the Vitamin D Receptor: Potentially the Link between Vitamin D, Immune Cells, and Multiple Sclerosis

Vitamin D has a plethora of functions that are important for the maintenance of general health and in particular, the functional integrity of the immune system, such as promoting an anti-inflammatory cytokine profile and reducing the Treg/Th17 ratio. Multiple sclerosis (MS) is a chronic, inflammatory, and neurodegenerative central nervous system (CNS) disorder of probable autoimmune origin. MS is characterized by recurring or progressive demyelination and degeneration of the CNS due in part to a misguided immune response to as yet undefined (CNS) antigens, potentially including myelin basic protein and proteolipid protein. MS has also been shown to be associated significantly with environmental factors such as the lack of vitamin D. The role of vitamin D in the pathogenesis and progression of MS is complex. Recent genetic studies have shown that various common MS-associated risk-single-nucleotide polymorphisms (SNPs) are located within or in the vicinity of genes associated with the complex metabolism of vitamin D. The functional aspects of these genetic associations may be explained either by a direct SNP-associated loss- or gain-of-function in a vitamin D-associated gene or due to a change in the regulation of gene expression in certain immune cell types. The development of new genetic tools using next-generation sequencing: e.g., chromatin immunoprecipitation sequencing (ChIP-seq) and the accompanying rapid progress of epigenomics has made it possible to recognize that the association between vitamin D and MS could be based on the extensive and characteristic genomic binding of the vitamin D receptor (VDR). Therefore, it is important to analyze comprehensively the spatiotemporal VDR binding patterns that have been identified using ChIP-seq in multiple immune cell types to reveal an integral profile of genomic VDR interaction. In summary, the aim of this review is to connect genomic effects vitamin D has on immune cells with MS and thus, to contribute to a better understanding of the influence of vitamin D on the etiology and the pathogenesis of this complex autoimmune disease.

Developmental plasticity: Bridging research in evolution and human health

Early life experiences can have profound and persistent effects on traits expressed throughout the life course, with consequences for later life behavior, disease risk, and mortality rates. The shaping of later life traits by early life environments, known as 'developmental plasticity', has been well-documented in humans and non-human animals, and has consequently captured the attention of both evolutionary biologists and researchers studying human health. Importantly, the parallel significance of developmental plasticity across multiple fields presents a timely opportunity to build a comprehensive understanding of this phenomenon. We aim to facilitate this goal by highlighting key outstanding questions shared by both evolutionary and health researchers, and by identifying theory and empirical work from both research traditions that is designed to address these questions. Specifically, we focus on: (i) evolutionary explanations for developmental plasticity, (ii) the genetics of developmental plasticity and (iii) the molecular mechanisms that mediate developmental plasticity. In each section, we emphasize the conceptual gains in human health and evolutionary biology that would follow from filling current knowledge gaps using interdisciplinary approaches. We encourage researchers interested in developmental plasticity to evaluate their own work in light of research from diverse fields, with the ultimate goal of establishing a cross-disciplinary understanding of developmental plasticity.

Shared genetic effects on chromatin and gene expression indicate a role for enhancer priming in immune response

Regulatory variants are often context specific, modulating gene expression in a subset of possible cellular states. Although these genetic effects can play important roles in disease, the molecular mechanisms underlying context specificity are poorly understood. Here, we identified shared quantitative trait loci (QTLs) for chromatin accessibility and gene expression in human macrophages exposed to IFNγ, Salmonella and IFNγ plus Salmonella. We observed that ~60% of stimulus-specific expression QTLs with a detectable effect on chromatin altered the chromatin accessibility in naive cells, thus suggesting that they perturb enhancer priming. Such variants probably influence binding of cell-type-specific transcription factors, such as PU.1, which can then indirectly alter the binding of stimulus-specific transcription factors, such as NF-κB or STAT2. Thus, although chromatin accessibility assays are powerful for fine-mapping causal regulatory variants, detecting their downstream effects on gene expression will be challenging, requiring profiling of large numbers of stimulated cellular states and time points.

Multiplexed droplet single-cell RNA-sequencing using natural genetic variation

Droplet single-cell RNA-sequencing (dscRNA-seq) has enabled rapid, massively parallel profiling of transcriptomes. However, assessing differential expression across multiple individuals has been hampered by inefficient sample processing and technical batch effects. Here we describe a computational tool, demuxlet, that harnesses natural genetic variation to determine the sample identity of each droplet containing a single cell (singlet) and detect droplets containing two cells (doublets). These capabilities enable multiplexed dscRNA-seq experiments in which cells from unrelated individuals are pooled and captured at higher throughput than in standard workflows. Using simulated data, we show that 50 single-nucleotide polymorphisms (SNPs) per cell are sufficient to assign 97% of singlets and identify 92% of doublets in pools of up to 64 individuals. Given genotyping data for each of eight pooled samples, demuxlet correctly recovers the sample identity of >99% of singlets and identifies doublets at rates consistent with previous estimates. We apply demuxlet to assess cell-type-specific changes in gene expression in 8 pooled lupus patient samples treated with interferon (IFN)-β and perform eQTL analysis on 23 pooled samples.

Resolving TYK2 locus genotype-to-phenotype differences in autoimmunity

Thousands of genetic variants have been identified, which contribute to the development of complex diseases, but determining how to elucidate their biological consequences for translation into clinical benefit is challenging. Conflicting evidence regarding the functional impact of genetic variants in the tyrosine kinase 2 (TYK2) gene, which is differentially associated with common autoimmune diseases, currently obscures the potential of TYK2 as a therapeutic target. We aimed to resolve this conflict by performing genetic meta-analysis across disorders; subsequent molecular, cellular, in vivo, and structural functional follow-up; and epidemiological studies. Our data revealed a protective homozygous effect that defined a signaling optimum between autoimmunity and immunodeficiency and identified TYK2 as a potential drug target for certain common autoimmune disorders.

Distinctive roles of age, sex, and genetics in shaping transcriptional variation of human immune responses to microbial challenges

Identifying the drivers of the interindividual diversity of the human immune system is crucial to understand their consequences on immune-mediated diseases. By examining the transcriptional responses of 1,000 individuals to various microbial challenges, we show that age and sex influence the expression of many immune-related genes, but their effects are overall moderate, whereas genetic factors affect a smaller gene set but with a stronger effect. We identify numerous genetic variants that affect transcriptional variation on infection, many of which are associated with autoimmune or inflammatory disorders. These results enable additional exploration of the role of regulatory variants in the pathogenesis of immune-related diseases and improve our understanding of the respective effects of age, sex, and genetics on immune response variation.

The contribution of host genetic and nongenetic factors to immunological differences in humans remains largely undefined. Here, we generated bacterial-, fungal-, and viral-induced immune transcriptional profiles in an age- and sex-balanced cohort of 1,000 healthy individuals and searched for the determinants of immune response variation. We found that age and sex affected the transcriptional response of most immune-related genes, with age effects being more stimulus-specific relative to sex effects, which were largely shared across conditions. Although specific cell populations mediated the effects of age and sex on gene expression, including CD8⁺ T cells for age and CD4⁺ T cells and monocytes for sex, we detected a direct effect of these intrinsic factors for the majority of immune genes. The mapping of expression quantitative trait loci (eQTLs) revealed that genetic factors had a stronger effect on immune gene regulation than age and sex, yet they affected a smaller number of genes. Importantly, we identified numerous genetic variants that manifested their regulatory effects exclusively on immune stimulation, including a Candida albicans-specific master regulator at the CR1 locus. These response eQTLs were enriched in disease-associated variants, particularly for autoimmune and inflammatory disorders, indicating that differences in disease risk may result from regulatory variants exerting their effects only in the presence of immune stress. Together, this study quantifies the respective effects of age, sex, genetics, and cellular heterogeneity on the interindividual variability of immune responses and constitutes a valuable resource for further exploration in the context of different infection risks or disease outcomes.

Robust classification of bacterial and viral infections via integrated host gene expression diagnostics

Improved diagnostics for acute infections could decrease morbidity and mortality by increasing early antibiotics for patients with bacterial infections and reducing unnecessary antibiotics for patients without bacterial infections. Several groups have used gene expression microarrays to build classifiers for acute infections, but these have been hampered by the size of the gene sets, use of overfit models, or lack of independent validation. We used multicohort analysis to derive a set of seven genes for robust discrimination of bacterial and viral infections, which we then validated in 30 independent cohorts. We next used our previously published 11-gene Sepsis MetaScore together with the new bacterial/viral classifier to build an integrated antibiotics decision model. In a pooled analysis of 1057 samples from 20 cohorts (excluding infants), the integrated antibiotics decision model had a sensitivity and specificity for bacterial infections of 94.0 and 59.8%, respectively (negative likelihood ratio, 0.10). Prospective clinical validation will be needed before these findings are implemented for patient care.

Immunogenomic approaches to understand the function of immune disease variants

Mapping hundreds of genetic variants through genome wide association studies provided an opportunity to gain insights into the pathobiology of immune-mediated diseases. However, as most of the disease variants fall outside the gene coding sequences the functional interpretation of the exact role of the associated variants remains to be determined. The integration of disease-associated variants with large scale genomic maps of cell-type-specific gene regulation at both chromatin and transcript levels deliver examples of functionally prioritized causal variants and genes. In particular, the enrichment of disease variants with histone marks can point towards the cell types most relevant to disease development. Furthermore, chromatin contact maps that link enhancers to promoter regions in a direct way allow the identification of genes that can be regulated by the disease variants. Candidate genes implicated with such approaches can be further examined through the correlation of gene expression with genotypes. Additionally, in the context of immune-mediated diseases it is important to combine genomics with immunology approaches. Genotype correlations with the immune system as a whole, as well as with cellular responses to different stimuli, provide a valuable platform for understanding the functional impact of disease-associated variants. The intersection of immunogenomic resources with disease-associated variants paints a detailed picture of disease causal mechanisms. Here, we provide an overview of recent studies that combine these approaches to identify disease vulnerable pathways.

iFORM/eQTL: an ultrahigh-dimensional platform for inferring the global genetic architecture of gene transcripts

Knowledge about how changes in gene expression are encoded by expression quantitative trait loci (eQTLs) is a key to construct the genotype-phenotype map for complex traits or diseases. Traditional eQTL mapping is to associate one transcript with a single marker at a time, thereby limiting our inference about a complete picture of the genetic architecture of gene expression. Here, we implemented an ultrahigh-dimensional variable selection model to build a computing platform that can systematically scan main effects and interaction effects among all possible loci and identify a set of significant eQTLs modulating differentiation and function of gene expression. This platform, named iFORM/eQTL, was assembled by forward-selection-based procedures to tackle complex covariance structures of gene-gene interactions. iFORM/eQTL can particularly discern the role of cis-QTLs, trans-QTLs and their epistatic interactions in gene expression. Results from the reanalysis of a published genetic and genomic data set through iFORM/eQTL gain new discoveries on the genetic origin of gene expression differentiation in Caenorhabditis elegans, which could not be detected by a traditional one-locus/one-transcript analysis approach.

Mechanisms of Pediatric Inflammatory Bowel Disease

Inflammatory bowel disease (IBD), including Crohn disease and ulcerative colitis, is characterized by chronic intestinal inflammation due to a complex interaction of genetic determinants, disruption of mucosal barriers, aberrant inflammatory signals, loss of tolerance, and environmental triggers. Importantly, the incidence of pediatric IBD is rising, particularly in children younger than 10 years. In this review, we discuss the clinical presentation of these patients and highlight environmental exposures that may affect disease risk, particularly among people with a background genetic risk. With regard to both children and adults, we review advancements in understanding the intestinal epithelium, the mucosal immune system, and the resident microbiota, describing how dysfunction at any level can lead to diseases like IBD. We conclude with future directions for applying advances in IBD genetics to better understand pathogenesis and develop therapeutics targeting key pathogenic nodes.

Sex influences eQTL effects of SLE and Sjögren's syndrome-associated genetic polymorphisms

BACKGROUND

Systemic lupus erythematosus (SLE) and primary Sjögren's syndrome (pSS) are autoimmune disorders characterized by autoantibodies, dysregulated B cells, and notably high female-to-male incidence ratios. Genome-wide association studies have identified several susceptibility SNPs for both diseases. Many SNPs in the genome are expression quantitative trait loci (eQTLs), with context-dependent effects. Assuming that sex is a biological context, we investigated whether SLE/pSS SNPs act as eQTLs in B cells and used a disease-targeted approach to understand if they display sex-specific effects.

METHODS

We used genome-wide genotype and gene expression data from primary B cells from 125 males and 162 females. The MatrixEQTL R package was used to identify eQTLs within a genomic window of 2 Mb centered on each of 22 established SLE and/or pSS susceptibility SNPs. To find sex-specific eQTLs, we used a linear model with a SNP * sex interaction term.

RESULTS

We found ten SNPs affecting the expression of 16 different genes (FDR < 0.05). rs7574865-INPP1, rs7574865-MYO1B, rs4938573-CD3D, rs11755393-SNRPC, and rs4963128-PHRF1 were novel observations for the immune compartment and B cells. By analyzing the SNP * sex interaction terms, we identified six genes with differentially regulated expression in females compared to males, depending on the genotype of SLE/pSS-associated SNPs: SLC39A8 (BANK1 locus), CD74 (TNIP1 locus), PXK, CTSB (BLK/FAM167A locus), ARCN1 (CXCR5 locus), and DHX9 (NCF2 locus).

CONCLUSIONS

We identified several unknown sex-specific eQTL effects of SLE/pSS-associated genetic polymorphisms and provide novel insight into how gene-sex interactions may contribute to the sex bias in systemic autoimmune diseases.

Reconstructing the Molecular Function of Genetic Variation in Regulatory Networks

Over the past decade, genetic studies have recognized hundreds of polymorphic DNA loci called response QTLs (reQTLs) as potential contributors to interindividual variation in transcriptional responses to stimulations. Such reQTLs commonly affect the transduction of signals along the regulatory network that controls gene transcription. Identifying the pathways through which reQTLs perturb the underlying network has been a major challenge. Here, we present GEVIN ("Genome-wide Embedding of Variation In Networks"), a methodology that simultaneously identifies a reQTL and the particular pathway in which the reQTL affects downstream signal transduction along the network. Using synthetic data, we show that this algorithm outperforms existing pathway identification and reQTL identification methods. We applied GEVIN to the analysis of murine and human dendritic cells in response to pathogenic components. These analyses revealed significant reQTLs together with their perturbed Toll-like receptor signaling pathways. GEVIN thus offers a powerful framework that renders a comprehensive picture of disease-related DNA loci and their molecular functions within regulatory networks.

Immune cell type 'fingerprints' at the basis of outcome diversity of human infection

Despite the availability of antibiotics and immunization, infectious diseases remain a major cause of malignancy and death worldwide. Yet, it is well documented that for most infectious agents, clinical disease develops in only a small minority of infected individuals. There is, in fact, great heterogeneity in infection outcome, from complete clearance of the pathogen to severe illness. Understanding this variation remains elusive, despite its great potential to equip us with new tools for the treatment of infectious diseases. Here, we propose a novel perspective for studying this diversity in human infection outcome, one that utilizes single-cell analysis technologies. Recent advances in single-cell RNA-seq technologies allow the detection of rare subpopulations that play important roles in host-pathogen interactions. We propose that applying single-cell RNA-seq to the study of infection can provide a 'fingerprint' of the immune cell types that are associated with the ability of the host to clear a pathogen and, thereby, broaden our current understanding of variation in susceptibility to infection within the population.

Landscape of X chromosome inactivation across human tissues

X chromosome inactivation (XCI) silences transcription from one of the two X chromosomes in female mammalian cells to balance expression dosage between XX females and XY males. XCI is, however, incomplete in humans: up to one-third of X-chromosomal genes are expressed from both the active and inactive X chromosomes (Xa and Xi, respectively) in female cells, with the degree of 'escape' from inactivation varying between genes and individuals. The extent to which XCI is shared between cells and tissues remains poorly characterized, as does the degree to which incomplete XCI manifests as detectable sex differences in gene expression and phenotypic traits. Here we describe a systematic survey of XCI, integrating over 5,500 transcriptomes from 449 individuals spanning 29 tissues from GTEx (v6p release) and 940 single-cell transcriptomes, combined with genomic sequence data. We show that XCI at 683 X-chromosomal genes is generally uniform across human tissues, but identify examples of heterogeneity between tissues, individuals and cells. We show that incomplete XCI affects at least 23% of X-chromosomal genes, identify seven genes that escape XCI with support from multiple lines of evidence and demonstrate that escape from XCI results in sex biases in gene expression, establishing incomplete XCI as a mechanism that is likely to introduce phenotypic diversity. Overall, this updated catalogue of XCI across human tissues helps to increase our understanding of the extent and impact of the incompleteness in the maintenance of XCI.

Updates in Lupus Genetics

PURPOSE OF REVIEW

Our understanding on genetic basis of SLE has been advanced through genome-wide association studies. We review recent progress in lupus genetics with a focus on SLE-associated loci that have been functionally characterized, and discuss the potential for clinical translation of genetics data.

RECENT FINDINGS

Over 100 loci have been confirmed to show robust association with SLE and many share with other immune-mediated diseases. Although causative variants captured at these established loci are limited, they guide biological studies of gene targets for functional characterization which highlight the importance of aberrant recognition of self-nucleic acid, type I interferon overproduction, and defective immune cell signaling underlying the pathogenesis of SLE. Increasing examples illustrate a predictive value of genetic findings in susceptibility/prognosis prediction, clinical classification, and pharmacological implication. Genetic findings provide a foundation for better understanding of disease pathogenic mechanisms and opportunities for target selection in lupus drug development.

Context-specific effects of genetic variants associated with autoimmune disease

Autoimmune diseases such as rheumatoid arthritis and coeliac disease are typical examples of complex genetic diseases caused by a combination of genetic and non-genetic risk factors. Insight into the genetic risk factors (single nucleotide polymorphisms (SNPs)) has increased since genome-wide association studies (GWAS) became possible in 2007 and, for individual diseases, SNPs can now explain some 15-50% of genetic risk. GWAS have also shown that some 50% of the genetic risk factors for individual autoimmune diseases overlap between different diseases. Thus, shared risk factors may converge to pathways that, when perturbed by genetic variation, predispose to autoimmunity in general. This raises the question of what determines disease specificity, and suggests that identical risk factors may have different effects in various autoimmune diseases. Addressing this question requires translation of genetic risk factors to causal genes and then to molecular and cellular pathways. Since >90% of the genetic risk factors are found in the non-coding part of the genome (i.e. outside the exons of protein-coding genes) and can have an impact on gene regulation, there is an urgent need to better understand the non-coding part of the genome. Here, we will outline the methods being used to unravel the gene regulatory networks perturbed in autoimmune diseases and the importance of doing this in the relevant cell types. We will highlight findings in coeliac disease, which manifests in the small intestine, to demonstrate how cell type and disease context can impact on the consequences of genetic risk factors.

Incorporation of Biological Knowledge Into the Study of Gene-Environment Interactions

A growing knowledge base of genetic and environmental information has greatly enabled the study of disease risk factors. However, the computational complexity and statistical burden of testing all variants by all environments has required novel study designs and hypothesis-driven approaches. We discuss how incorporating biological knowledge from model organisms, functional genomics, and integrative approaches can empower the discovery of novel gene-environment interactions and discuss specific methodological considerations with each approach. We consider specific examples where the application of these approaches has uncovered effects of gene-environment interactions relevant to drug response and immunity, and we highlight how such improvements enable a greater understanding of the pathogenesis of disease and the realization of precision medicine.

Interferon-γ Represses M2 Gene Expression in Human Macrophages by Disassembling Enhancers Bound by the Transcription Factor MAF

Mechanisms by which interferon (IFN)-γ activates genes to promote macrophage activation are well studied, but little is known about mechanisms and functions of IFN-γ-mediated gene repression. We used an integrated transcriptomic and epigenomic approach to analyze chromatin accessibility, histone modifications, transcription-factor binding, and gene expression in IFN-γ-primed human macrophages. IFN-γ suppressed basal expression of genes corresponding to an "M2"-like homeostatic and reparative phenotype. IFN-γ repressed genes by suppressing the function of enhancers enriched for binding by transcription factor MAF. Mechanistically, IFN-γ disassembled a subset of enhancers by inducing coordinate suppression of binding by MAF, lineage-determining transcription factors, and chromatin accessibility. Genes associated with MAF-binding enhancers were suppressed in macrophages isolated from rheumatoid-arthritis patients, revealing a disease-associated signature of IFN-γ-mediated repression. These results identify enhancer inactivation and disassembly as a mechanism of IFN-γ-mediated gene repression and reveal that MAF regulates the macrophage enhancer landscape and is suppressed by IFN-γ to augment macrophage activation.

Standardized whole blood stimulation improves immunomonitoring of induced immune responses in multi-center study

Functional immune responses are increasingly important for clinical studies, providing in depth biomarker information to assess immunotherapy or vaccination. Incorporating functional immune assays into routine clinical practice has remained limited due to challenges in standardizing sample preparation. We recently described the use of a whole blood syringe-based system, TruCulture®, which permits point-of-care standardized immune stimulation. Here, we report on a multi-center clinical study in seven FOCIS Centers of Excellence to directly compare TruCulture to conventional PBMC methods. Whole blood and PBMCs from healthy donors were exposed to LPS, anti-CD3 anti-CD28 antibodies, or media alone. 55 protein analytes were analyzed centrally by Luminex multi-analyte profiling in a CLIA-certified laboratory. TruCulture responses showed greater reproducibility and improved the statistical power for monitoring differential immune response activation. The use of TruCulture addresses a major unmet need through a robust and flexible method for immunomonitoring that can be reproducibly applied in multi-center clinical studies.

ONE SENTENCE SUMMARY

A multi-center study revealed greater reproducibility from whole blood stimulation systems as compared to PBMC stimulation for studying induced immune responses.

Systematic Analysis of Cell-to-Cell Expression Variation of T Lymphocytes in a Human Cohort Identifies Aging and Genetic Associations

Cell-to-cell expression variation (CEV) is a prevalent feature of even well-defined cell populations, but its functions, particularly at the organismal level, are not well understood. Using single-cell data obtained via high-dimensional flow cytometry of T cells as a model, we introduce an analysis framework for quantifying CEV in primary cell populations and studying its functional associations in human cohorts. Analyses of 840 CEV phenotypes spanning multiple baseline measurements of 14 proteins in 28 T cell subpopulations suggest that the quantitative extent of CEV can exhibit substantial subject-to-subject differences and yet remain stable within healthy individuals over months. We linked CEV to age and disease-associated genetic polymorphisms, thus implicating CEV as a biomarker of aging and disease susceptibility and suggesting that it might play an important role in health and disease. Our dataset, interactive figures, and software for computing CEV with flow cytometry data provide a resource for exploring CEV functions.

Human genetic variation in VAC14 regulates Salmonella invasion and typhoid fever through modulation of cholesterol

Risk, severity, and outcome of infection depend on the interplay of pathogen virulence and host susceptibility. Systematic identification of genetic susceptibility to infection is being undertaken through genome-wide association studies, but how to expeditiously move from genetic differences to functional mechanisms is unclear. Here, we use genetic association of molecular, cellular, and human disease traits and experimental validation to demonstrate that genetic variation affects expression of VAC14, a phosphoinositide-regulating protein, to influence susceptibility to Salmonella enterica serovar Typhi (S Typhi) infection. Decreased VAC14 expression increased plasma membrane cholesterol, facilitating Salmonella docking and invasion. This increased susceptibility at the cellular level manifests as increased susceptibility to typhoid fever in a Vietnamese population. Furthermore, treating zebrafish with a cholesterol-lowering agent, ezetimibe, reduced susceptibility to S Typhi. Thus, coupling multiple genetic association studies with mechanistic dissection revealed how VAC14 regulates Salmonella invasion and typhoid fever susceptibility and may open doors to new prophylactic/therapeutic approaches.

Genetic regulatory effects modified by immune activation contribute to autoimmune disease associations

The immune system plays a major role in human health and disease, and understanding genetic causes of interindividual variability of immune responses is vital. Here, we isolate monocytes from 134 genotyped individuals, stimulate these cells with three defined microbe-associated molecular patterns (LPS, MDP, and 5'-ppp-dsRNA), and profile the transcriptomes at three time points. Mapping expression quantitative trait loci (eQTL), we identify 417 response eQTLs (reQTLs) with varying effects between conditions. We characterize the dynamics of genetic regulation on early and late immune response and observe an enrichment of reQTLs in distal cis-regulatory elements. In addition, reQTLs are enriched for recent positive selection with an evolutionary trend towards enhanced immune response. Finally, we uncover reQTL effects in multiple GWAS loci and show a stronger enrichment for response than constant eQTLs in GWAS signals of several autoimmune diseases. This demonstrates the importance of infectious stimuli in modifying genetic predisposition to disease.Insight into the genetic influence on the immune response is important for the understanding of interindividual variability in human pathologies. Here, the authors generate transcriptome data from human blood monocytes stimulated with various immune stimuli and provide a time-resolved response eQTL map.

Deciphering the genetic control of gene expression following Mycobacterium leprae antigen stimulation

Leprosy is a human infectious disease caused by Mycobacterium leprae. A strong host genetic contribution to leprosy susceptibility is well established. However, the modulation of the transcriptional response to infection and the mechanism(s) of disease control are poorly understood. To address this gap in knowledge of leprosy pathogenicity, we conducted a genome-wide search for expression quantitative trait loci (eQTL) that are associated with transcript variation before and after stimulation with M. leprae sonicate in whole blood cells. We show that M. leprae antigen stimulation mainly triggered the upregulation of immune related genes and that a substantial proportion of the differential gene expression is genetically controlled. Indeed, using stringent criteria, we identified 318 genes displaying cis-eQTL at an FDR of 0.01, including 66 genes displaying response-eQTL (reQTL), i.e. cis-eQTL that showed significant evidence for interaction with the M. leprae stimulus. Such reQTL correspond to regulatory variations that affect the interaction between human whole blood cells and M. leprae sonicate and, thus, likely between the human host and M. leprae bacilli. We found that reQTL were significantly enriched among binding sites of transcription factors that are activated in response to infection, and that they were enriched among single nucleotide polymorphisms (SNPs) associated with susceptibility to leprosy per se and Type-I Reaction, and seven of them have been targeted by recent positive selection. Our study suggested that natural selection shaped our genomic diversity to face pathogen exposure including M. leprae infection.

Each year, 200,000 new leprosy cases are reported worldwide. While there is unambiguous evidence for a role of host genetics in leprosy pathogenesis, the mechanisms by which the human host fights the infection are poorly understood. Here, we highlight the search for naturally occurring genetic variations that modulate gene expression levels following exposure to sonicate of Mycobacterium leprae, the bacterium causing the disease. Because M. leprae is not cultivable and the genuine immune cells involved in the host response during infection are still unknown, we performed a genome-wide search for such genetic variations after stimulation of whole-blood from leprosy patients with M. leprae sonicate. This design allowed to provide a general framework for the genetic control of host responses to M. leprae and outlined the contribution of host genetics to leprosy pathogenesis. Among the M. leprae-dependent genetic regulators of gene expression levels there was an enrichment of variants (i) associated with leprosy, (ii) located in transcription factor binding sites and (iii) targeted by recent positive selection.

Molecular and genetic inflammation networks in major human diseases

It has been well-recognized that inflammation alongside tissue repair and damage maintaining tissue homeostasis determines the initiation and progression of complex diseases. Albeit with the accomplishment of having captured the most critical inflammation-involved molecules, genetic susceptibilities, epigenetic factors, and environmental factors, our schemata on the role of inflammation in complex diseases remain largely patchy, in part due to the success of reductionism in terms of research methodology per se. Omics data alongside the advances in data integration technologies have enabled reconstruction of molecular and genetic inflammation networks which shed light on the underlying pathophysiology of complex diseases or clinical conditions. Given the proven beneficial role of anti-inflammation in coronary heart disease as well as other complex diseases and immunotherapy as a revolutionary transition in oncology, it becomes timely to review our current understanding of the molecular and genetic inflammation networks underlying major human diseases. In this review, we first briefly discuss the complexity of infectious diseases and then highlight recently uncovered molecular and genetic inflammation networks in other major human diseases including obesity, type II diabetes, coronary heart disease, late onset Alzheimer's disease, Parkinson's disease, and sporadic cancer. The commonality and specificity of these molecular networks are addressed in the context of genetics based on genome-wide association study (GWAS). The double-sword role of inflammation, such as how the aberrant type 1 and/or type 2 immunity leads to chronic and severe clinical conditions, remains open in terms of the inflammasome and the core inflammatome network features. Increasingly available large Omics and clinical data in tandem with systems biology approaches have offered an exciting yet challenging opportunity toward reconstruction of more comprehensive and dynamic molecular and genetic inflammation networks, which hold great promise in transiting network snapshots to video-style multi-scale interplays of disease mechanisms, in turn leading to effective clinical intervention.

SNP-mediated disruption of CTCF binding at the IFITM3 promoter is associated with risk of severe influenza in humans

Previous studies have reported associations of IFITM3 SNP rs12252 with severe influenza, but evidence of association and the mechanism by which risk is conferred remain controversial. We prioritized SNPs in IFITM3 on the basis of putative biological function and identified rs34481144 in the 5' UTR. We found evidence of a new association of rs34481144 with severe influenza in three influenza-infected cohorts characterized by different levels of influenza illness severity. We determined a role for rs34481144 as an expression quantitative trait locus (eQTL) for IFITM3, with the risk allele associated with lower mRNA expression. The risk allele was found to have decreased IRF3 binding and increased CTCF binding in promoter-binding assays, and risk allele carriage diminished transcriptional correlations among IFITM3-neighboring genes, indicative of CTCF boundary activity. Furthermore, the risk allele disrupts a CpG site that undergoes differential methylation in CD8⁺ T cell subsets. Carriers of the risk allele had reduced numbers of CD8⁺ T cells in their airways during natural influenza infection, consistent with IFITM3 promoting accumulation of CD8⁺ T cells in airways and indicating that a critical function for IFITM3 may be to promote immune cell persistence at mucosal sites.Our study identifies a new regulator of IFITM3 expression that associates with CD8⁺ T cell levels in the airways and a spectrum of clinical outcomes.

Type-I interferon pathway in neuroinflammation and neurodegeneration: focus on Alzheimer's disease

Past research in Alzheimer's disease (AD) has largely been driven by the amyloid hypothesis; the accompanying neuroinflammation seen in AD has been assumed to be consequential and not disease modifying or causative. However, recent data from both clinical and preclinical studies have established that the immune-driven neuroinflammation contributes to AD pathology. Key evidence for the involvement of neuroinflammation in AD includes enhanced microglial and astroglial activation in the brains of AD patients, increased pro-inflammatory cytokine burden in AD brains, and epidemiological evidence that chronic non-steroidal anti-inflammatory drug use prior to disease onset leads to a lower incidence of AD. Identifying critical mediators controlling this neuroinflammation will prove beneficial in developing anti-inflammatory therapies for the treatment of AD. The type-I interferons (IFNs) are pleiotropic cytokines that control pro-inflammatory cytokine secretion and are master regulators of the innate immune response that impact on disorders of the central nervous system. This review provides evidence that the type-I IFNs play a critical role in the exacerbation of neuroinflammation and actively contribute to the progression of AD.

Inflammasomes and intestinal inflammation

The inflammasome is a cytosolic multi-protein innate immune rheostat, sensing a variety of endogenous and environmental stimuli, and regulating homeostasis or damage control. In the gastrointestinal tract, inflammasomes orchestrate immune tolerance to microbial and potentially food-related signals or drive the initiation of inflammatory responses to invading pathogens. When inadequately regulated, intestinal inflammasome activation leads to a perpetuated inflammatory response leading to immune pathology and tissue damage. In this review, we present the main features of the predominant types of inflammasomes participating in intestinal homeostasis and inflammation. We then discuss current controversies and open questions related to their functions and implications in disease, highlighting how pathological inflammasome over-activation or impaired function impact gut homeostasis, the microbiome ecosystem, and the propensity to develop gut-associated diseases. Collectively, understanding of the molecular basis of intestinal inflammasome signaling may be translated into clinical manipulation of this fundamental pathway as a potential immune modulatory therapeutic intervention.

Effects of Type 1 Diabetes Risk Alleles on Immune Cell Gene Expression

Genetic studies have identified 61 variants associated with the risk of developing Type 1 Diabetes (T1D). The functions of most of the non-HLA (Human Leukocyte Antigen) genetic variants remain unknown. We found that only 16 of these risk variants could potentially be linked to a protein-coding change. Therefore, we investigated whether these variants affected susceptibility by regulating changes in gene expression. To do so, we examined whole transcriptome profiles of 600 samples from the Type 1 Diabetes Genetics Consortium (T1DGC). These comprised four different immune cell types (Epstein-Barr virus (EBV)-transformed B cells, either basal or after stimulation; and cluster of differentiation (CD)4+ and CD8+ T cells). Many of the T1D-associated risk variants regulated expression of either neighboring (cis-) or distant (trans-) genes. In brief, 24 of the non-HLA T1D variants affected the expression of 31 nearby genes (cis) while 25 affected 38 distant genes (trans). The effects were highly significant (False Discovery Rate p < 0.001). In addition, we searched in public databases for expression effects of T1D single nucleotide polymorphisms (SNPs) in other immune cell types such as CD14+ monocytes, lipopolysaccharide (LPS) stimulated monocytes, and CD19+ B cells. In this paper, we review the (expression quantitative trait loci (eQTLs) associated with each of the 60 T1D variants and provide a summary of the genes impacted by T1D risk alleles in various immune cells. We then review the methodological steps involved in analyzing the function of genome wide association studies (GWAS)-identified variants, with emphasis on those affecting gene expression. We also discuss recent advancements in the methodologies and their advantages. We conclude by suggesting future study designs that will aid in the study of T1D risk variants.

Guanabenz Prevents d-Galactosamine/Lipopolysaccharide-Induced Liver Damage and Mortality

Multi-organ failure in response to uncontrolled microbial infection is characterized by low blood pressure accompanied by a systemic over-inflammation state, caused by massive pro-inflammatory cytokines release and liver damage. Recently, the integrated stress response (ISR), characterized by eukaryotic translation initiation factor 2α (eIF2α) phosphorylation, was involved with controlling apoptosis in stressed hepatocytes and associated with poor survival to endotoxin challenge. Lipopolysaccharide (LPS) alone is able to induce the ISR in hepatocytes and can trigger massive liver damage along with tumor necrosis factor-alpha (TNF-α) expression. Consequently, drugs interfering with eIF2α phosphorylation may represent potential candidates for the treatment of such pathologies. We, therefore, used Guanabenz (GBZ), a small compound with enhancing eIF2α phosphorylation activity to evaluate its effect on bacterial LPS sensing and endotoxemia. GBZ is confirmed here to have an anti-inflammatory activity by increasing in vitro interleukin-10 (IL-10) production by LPS-stimulated dendritic cells. We further show that in the d-galactosamine (d-galN)/LPS-dependent lethality model, intraperitoneal injection of GBZ promoted mice survival, prevented liver damage, increased IL-10 levels, and inhibited TNF-α production. GBZ and its derivatives could therefore represent an interesting pharmacological solution to control systemic inflammation and associated acute liver failure.

Allele-specific expression reveals interactions between genetic variation and environment

Identifying interactions between genetics and the environment (GxE) remains challenging. We have developed EAGLE, a hierarchical Bayesian model for identifying GxE interactions based on association between environment and allele-specific expression (ASE). Combining RNA-sequencing of whole blood and extensive environmental annotations collected from 922 human individuals, we identified 35 GxE interactions, compared to only four using standard GxE testing. EAGLE provides new opportunities to identify GxE interactions using functional genomic data.

An independent component analysis confounding factor correction framework for identifying broad impact expression quantitative trait loci

Genome-wide expression Quantitative Trait Loci (eQTL) studies in humans have provided numerous insights into the genetics of both gene expression and complex diseases. While the majority of eQTL identified in genome-wide analyses impact a single gene, eQTL that impact many genes are particularly valuable for network modeling and disease analysis. To enable the identification of such broad impact eQTL, we introduce CONFETI: Confounding Factor Estimation Through Independent component analysis. CONFETI is designed to address two conflicting issues when searching for broad impact eQTL: the need to account for non-genetic confounding factors that can lower the power of the analysis or produce broad impact eQTL false positives, and the tendency of methods that account for confounding factors to model broad impact eQTL as non-genetic variation. The key advance of the CONFETI framework is the use of Independent Component Analysis (ICA) to identify variation likely caused by broad impact eQTL when constructing the sample covariance matrix used for the random effect in a mixed model. We show that CONFETI has better performance than other mixed model confounding factor methods when considering broad impact eQTL recovery from synthetic data. We also used the CONFETI framework and these same confounding factor methods to identify eQTL that replicate between matched twin pair datasets in the Multiple Tissue Human Expression Resource (MuTHER), the Depression Genes Networks study (DGN), the Netherlands Study of Depression and Anxiety (NESDA), and multiple tissue types in the Genotype-Tissue Expression (GTEx) consortium. These analyses identified both cis-eQTL and trans-eQTL impacting individual genes, and CONFETI had better or comparable performance to other mixed model confounding factor analysis methods when identifying such eQTL. In these analyses, we were able to identify and replicate a few broad impact eQTL although the overall number was small even when applying CONFETI. In light of these results, we discuss the broad impact eQTL that have been previously reported from the analysis of human data and suggest that considerable caution should be exercised when making biological inferences based on these reported eQTL.

Type I interferon signaling in systemic immune cells from patients with alcoholic cirrhosis and its association with outcome

BACKGROUND & AIMS

In immune cells, constitutively and acutely produced type I interferons (IFNs) engage autocrine/paracrine signaling pathways to induce IFN-stimulated genes (ISGs). Enhanced activity of IFN signaling pathways can cause excessive inflammation and tissue damage. We aimed to investigate ISG expression in systemic immune cells from patients with decompensated alcoholic cirrhosis, and its association with outcome.

METHODS

Peripheral blood mononuclear cells (PBMCs) from patients and heathy subjects were stimulated or not with lipopolysaccharide (LPS, an IFN inducer) or increasing concentrations of IFN-β. The expression of 48 ISGs and ten "non-ISG" inflammatory cytokines were analyzed using RT-qPCR.

RESULTS

We developed an 8-ISG signature (IFN score) assessing ISG expression. LPS-stimulated ISG induction was significantly lower in PBMCs from patients with cirrhosis compared to healthy controls. Non-ISGs, however, showed higher induction. Lower induction of ISGs by LPS was not due to decreased IFN production by cirrhotic PBMCs or neutralization of secreted IFN, but a defective PBMC response to IFN. This defect was at least in part due to decreased constitutive ISG expression. Patients with the higher baseline IFN scores and ISG levels had the higher risk of death. At baseline, "non-ISG" cytokines did not correlate with outcome.

CONCLUSIONS

PBMCs from patients with decompensated alcoholic cirrhosis exhibit downregulated ISG expression, both constitutively and after an acute stimulus. Our finding that higher baseline PBMC ISG expression was associated with higher risk of death, suggests that constitutive ISG expression in systemic immune cells contributes to the prognosis of alcoholic cirrhosis.

LAY SUMMARY

Enhanced activity of IFN signaling pathways can cause excessive inflammation and tissue damage. Here we show that peripheral blood mononuclear cells (PBMCs) from patients with alcoholic cirrhosis exhibit a defect in interferon-stimulated genes (ISGs). We found that higher baseline ISG expression in PBMCs was associated with higher risk of death, revealing a probable contribution of ISG expression in immune cells to the outcome of alcoholic cirrhosis.

Single-cell RNA-seq reveals new types of human blood dendritic cells, monocytes, and progenitors

Dendritic cells (DCs) and monocytes play a central role in pathogen sensing, phagocytosis, and antigen presentation and consist of multiple specialized subtypes. However, their identities and interrelationships are not fully understood. Using unbiased single-cell RNA sequencing (RNA-seq) of ~2400 cells, we identified six human DCs and four monocyte subtypes in human blood. Our study reveals a new DC subset that shares properties with plasmacytoid DCs (pDCs) but potently activates T cells, thus redefining pDCs; a new subdivision within the CD1C+ subset of DCs; the relationship between blastic plasmacytoid DC neoplasia cells and healthy DCs; and circulating progenitor of conventional DCs (cDCs). Our revised taxonomy will enable more accurate functional and developmental analyses as well as immune monitoring in health and disease.

The Multiple Sclerosis (MS) Genetic Risk Factors Indicate both Acquired and Innate Immune Cell Subsets Contribute to MS Pathogenesis and Identify Novel Therapeutic Opportunities

Multiple sclerosis (MS) is known to be a partially heritable autoimmune disease. The risk of developing MS increases from typically 1 in 1,000 in the normal population to 1 in 4 or so for identical twins where one twin is affected. Much of this heritability is now explained and is due almost entirely to genes affecting the immune response. The largest and first identified genetic risk factor is an allele from the MHC class II HLA-DRB1 gene, HLA-DRB1*15:01, which increases risk about threefold. The HLA-DRB1 gene is expressed in antigen-presenting cells, and its protein functions in presenting particular types of antigen to CD4 T cells. This discovery supported the development of the first successful immunomodulatory therapies: glatiramer acetate, which mimics the antigen presentation process, and interferon beta, which targets CD4 T cell activation. Over 200 genetic risk variants, all single nucleotide polymorphisms (SNPs), have now been described. The SNPs are located within, or close to, genes expressed predominantly in acquired and innate immune cell subsets, indicating that both contribute to MS pathogenesis. The risk alleles indicate variation in the regulation of gene expression, rather than protein variation, underpins genetic susceptibility. In this review, we discuss how the expression and function of the risk genes, as well as the effect on these of the risk SNPs, indicate specific acquired immune cell processes that are the target of current successful therapies, and also point to novel therapeutic approaches.

Linking the Human Gut Microbiome to Inflammatory Cytokine Production Capacity

Gut microbial dysbioses are linked to aberrant immune responses, which are often accompanied by abnormal production of inflammatory cytokines. As part of the Human Functional Genomics Project (HFGP), we investigate how differences in composition and function of gut microbial communities may contribute to inter-individual variation in cytokine responses to microbial stimulations in healthy humans. We observe microbiome-cytokine interaction patterns that are stimulus specific, cytokine specific, and cytokine and stimulus specific. Validation of two predicted host-microbial interactions reveal that TNFα and IFNγ production are associated with specific microbial metabolic pathways: palmitoleic acid metabolism and tryptophan degradation to tryptophol. Besides providing a resource of predicted microbially derived mediators that influence immune phenotypes in response to common microorganisms, these data can help to define principles for understanding disease susceptibility. The three HFGP studies presented in this issue lay the groundwork for further studies aimed at understanding the interplay between microbial, genetic, and environmental factors in the regulation of the immune response in humans. PAPERCLIP.

Host and Environmental Factors Influencing Individual Human Cytokine Responses

Differences in susceptibility to immune-mediated diseases are determined by variability in immune responses. In three studies within the Human Functional Genomics Project, we assessed the effect of environmental and non-genetic host factors of the genetic make-up of the host and of the intestinal microbiome on the cytokine responses in humans. We analyzed the association of these factors with circulating mediators and with six cytokines after stimulation with 19 bacterial, fungal, viral, and non-microbial metabolic stimuli in 534 healthy subjects. In this first study, we show a strong impact of non-genetic host factors (e.g., age and gender) on cytokine production and circulating mediators. Additionally, annual seasonality is found to be an important environmental factor influencing cytokine production. Alpha-1-antitrypsin concentrations partially mediate the seasonality of cytokine responses, whereas the effect of vitamin D levels is limited. The complete dataset has been made publicly available as a comprehensive resource for future studies. PAPERCLIP.

Living in an adaptive world: Genomic dissection of the genus Homo and its immune response

More than a decade after the sequencing of the human genome, a deluge of genome-wide population data are generating a portrait of human genetic diversity at an unprecedented level of resolution. Genomic studies have provided new insight into the demographic and adaptive history of our species, Homo sapiens, including its interbreeding with other hominins, such as Neanderthals, and the ways in which natural selection, in its various guises, has shaped genome diversity. These studies, combined with functional genomic approaches, such as the mapping of expression quantitative trait loci, have helped to identify genes, functions, and mechanisms of prime importance for host survival and involved in phenotypic variation and differences in disease risk. This review summarizes new findings in this rapidly developing field, focusing on the human immune response. We discuss the importance of defining the genetic and evolutionary determinants driving immune response variation, and highlight the added value of population genomic approaches in settings relevant to immunity and infection.

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.