Peter Humburg

Innate Immune Activity Conditions the Effect of Regulatory Variants upon Monocyte Gene Expression

Introduction Many genetic variants associated with common disease susceptibility occur close to immune-related genes in noncoding DNA, suggestive of a regulatory function. The definition of functional variants and the specific genes that they regulate remains challenging and in many cases is unresolved. We hypothesized that a significant proportion of variants, including those implicated in disease, may show activity in a context-specific manner and therefore only be identifiable upon triggering of immune responses. Context-specific genetic association with differential gene expression in IFN-β signaling. (A) A local association (cis-eQTL) with IFNB1 expression for a single-nucleotide polymorphism (rs2275888) revealed after 2 hours of LPS stimulation of monocytes. (B) This genetic marker shows association with expression of 17 genes on different chromosomes (trans-eQTLs) after 24 hours of LPS stimulation, forming a gene network (C) consistent with the IFN-β signaling cascade. Methods We mapped interindividual variation in gene expression as a quantitative trait, defining expression quantitative trait loci (eQTLs). To investigate the effect of innate immune stimuli on eQTLs, we exposed primary CD14+ human monocytes from 432 European volunteers to the inflammatory proxies interferon-γ (IFN-γ) or differing durations (2 or 24 hours) of lipopolysaccharide (LPS). eQTL mapping was performed on a genome-wide basis with an additive linear model. A subset of 228 individuals with expression data available for all experimental conditions enabled cross-treatment comparisons. Results Stimulation with LPS or IFN-γ resulted in profound effects across monocyte eQTLs, with hundreds of genes and associated pathways demonstrating context-specific eQTLs dependent on the type and duration of stimulus. Context-specific eQTLs frequently intersected established canonical pathways of monocyte signaling and included key nodal genes and effector molecules. These eQTLs are typically more distal to the transcriptional start site and, in some cases, showed reversal of effect between conditions. We also found stimulation reveals novel eQTLs with simultaneous effects involving many genes (trans-eQTLs). Examples included coding polymorphisms in CYP1B1, P2RY11, and IDO2 that modulate activity and develop trans network effects upon stimulation; an LPS-specific IFN-β cytokine network response driven by a cis-eQTL for IFNB1 that was only revealed over time; an interferon regulatory factor 2 (IRF2) transcription factor modulated network up-regulated by IFN-γ involving a cis-eQTL for IRF2; and an IFN-γ–inducible trans gene network involving the transcription factor NFE2L3. We find trans associations to the major histocompatibility complex are dependent on context, paralleling the expression of class II genes. Induced eQTLs were enriched for disease-risk loci with context-specific associations to many putative causal genes, including at ATM, IRF8, and CCR3. Conditional analysis defined additional independent stimulus-specific peaks of association for a given gene. For CARD9 we observed, in addition to a constitutive eQTL informative for a genome-wide association study locus for Crohn’s disease, a stimulus-specific peak eQTL after IFN-γ, defining a further independent signal of disease association. Discussion Interindividual variation in immune responses is accompanied by diverging patterns of gene regulation dependent on underlying genotype. In human monocytes, many regulatory variants display functionality only after pathophysiologically relevant immune stimuli. By considering the cellular and environmental context relevant to disease, it is possible to more extensively resolve functional genetic variants and the specific modulated genes associated with disease. Immune Variation It is difficult to determine the mechanistic consequences of context-dependent genetic variants, some of which may be related to disease (see the Perspective by Gregersen). Two studies now report on the effects of stimulating immunological monocytes and dendritic cells with proteins that can elicit a response to bacterial or viral infection and assess the functional links between genetic variants and profiles of gene expression. M. N. Lee et al. (10.1126/science.1246980) analyzed the expression of more than 400 genes, in dendritic cells from 30 healthy subjects, which revealed how expression quantitative trait loci (eQTLs) affect gene expression within the interferon-β and the Toll-like receptor 3 and 4 pathways. Fairfax et al. (10.1126/science.1246949) performed a genome-wide analysis to show that many eQTLs affected monocyte gene expression in a stimulus- or time-specific manner. Analysis of the transcriptional responses during induced innate immune activity in primary human monocytes is explained. [Also see Perspective by Gregersen] To systematically investigate the impact of immune stimulation upon regulatory variant activity, we exposed primary monocytes from 432 healthy Europeans to interferon-γ (IFN-γ) or differing durations of lipopolysaccharide and mapped expression quantitative trait loci (eQTLs). More than half of cis-eQTLs identified, involving hundreds of genes and associated pathways, are detected specifically in stimulated monocytes. Induced innate immune activity reveals multiple master regulatory trans-eQTLs including the major histocompatibility complex (MHC), coding variants altering enzyme and receptor function, an IFN-β cytokine network showing temporal specificity, and an interferon regulatory factor 2 (IRF2) transcription factor–modulated network. Induced eQTL are significantly enriched for genome-wide association study loci, identifying context-specific associations to putative causal genes including CARD9, ATM, and IRF8. Thus, applying pathophysiologically relevant immune stimuli assists resolution of functional genetic variants.

A Fine-Scale Chimpanzee Genetic Map from Population Sequencing

Going Ape Over Genetic Maps Recombination is an important process in generating diversity and producing selectively advantageous genetic combinations. Thus, changes in recombination hotspots may influence speciation. To investigate the variation in recombination processes in humans and their closest existing relatives, Auton et al. (p. 193, published online 15 March) prepared a fine-scale genetic map of the Western chimpanzee and compared it with that of humans. While rates of recombination are comparable between humans and chimpanzees, the locations and genetic motifs associated with recombination differ between the species. Chimpanzees show similar genetic recombination rates as humans but differ in the genomic regions involved. To study the evolution of recombination rates in apes, we developed methodology to construct a fine-scale genetic map from high-throughput sequence data from 10 Western chimpanzees, Pan troglodytes verus. Compared to the human genetic map, broad-scale recombination rates tend to be conserved, but with exceptions, particularly in regions of chromosomal rearrangements and around the site of ancestral fusion in human chromosome 2. At fine scales, chimpanzee recombination is dominated by hotspots, which show no overlap with those of humans even though rates are similarly elevated around CpG islands and decreased within genes. The hotspot-specifying protein PRDM9 shows extensive variation among Western chimpanzees, and there is little evidence that any sequence motifs are enriched in hotspots. The contrasting locations of hotspots provide a natural experiment, which demonstrates the impact of recombination on base composition.

Mosaic PPM1D mutations are associated with predisposition to breast and ovarian cancer

Improved sequencing technologies offer unprecedented opportunities for investigating the role of rare genetic variation in common disease. However, there are considerable challenges with respect to study design, data analysis and replication. Using pooled next-generation sequencing of 507 genes implicated in the repair of DNA in 1,150 samples, an analytical strategy focused on protein-truncating variants (PTVs) and a large-scale sequencing case–control replication experiment in 13,642 individuals, here we show that rare PTVs in the p53-inducible protein phosphatase PPM1D are associated with predisposition to breast cancer and ovarian cancer. PPM1D PTV mutations were present in 25 out of 7,781 cases versus 1 out of 5,861 controls (P = 1.12 × 10−5), including 18 mutations in 6,912 individuals with breast cancer (P = 2.42 × 10−4) and 12 mutations in 1,121 individuals with ovarian cancer (P = 3.10 × 10−9). Notably, all of the identified PPM1D PTVs were mosaic in lymphocyte DNA and clustered within a 370-base-pair region in the final exon of the gene, carboxy-terminal to the phosphatase catalytic domain. Functional studies demonstrate that the mutations result in enhanced suppression of p53 in response to ionizing radiation exposure, suggesting that the mutant alleles encode hyperactive PPM1D isoforms. Thus, although the mutations cause premature protein truncation, they do not result in the simple loss-of-function effect typically associated with this class of variant, but instead probably have a gain-of-function effect. Our results have implications for the detection and management of breast and ovarian cancer risk. More generally, these data provide new insights into the role of rare and of mosaic genetic variants in common conditions, and the use of sequencing in their identification.

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

Summary Background Effective targeted therapy for sepsis requires an understanding of the heterogeneity in the individual host response to infection. We investigated this heterogeneity by defining interindividual variation in the transcriptome of patients with sepsis and related this to outcome and genetic diversity. Methods We assayed peripheral blood leucocyte global gene expression for a prospective discovery cohort of 265 adult patients admitted to UK intensive care units with sepsis due to community-acquired pneumonia and evidence of organ dysfunction. We then validated our findings in a replication cohort consisting of a further 106 patients. We mapped genomic determinants of variation in gene transcription between patients as expression quantitative trait loci (eQTL). Findings We discovered that following admission to intensive care, transcriptomic analysis of peripheral blood leucocytes defines two distinct sepsis response signatures (SRS1 and SRS2). The presence of SRS1 (detected in 108 [41%] patients in discovery cohort) identifies individuals with an immunosuppressed phenotype that included features of endotoxin tolerance, T-cell exhaustion, and downregulation of human leucocyte antigen (HLA) class II. SRS1 was associated with higher 14 day mortality than was SRS2 (discovery cohort hazard ratio (HR) 2·4, 95% CI 1·3–4·5, p=0·005; validation cohort HR 2·8, 95% CI 1·5–5·1, p=0·0007). We found that a predictive set of seven genes enabled the classification of patients as SRS1 or SRS2. We identified cis-acting and trans-acting eQTL for key immune and metabolic response genes and sepsis response networks. Sepsis eQTL were enriched in endotoxin-induced epigenetic marks and modulated the individual host response to sepsis, including effects specific to SRS group. We identified regulatory genetic variants involving key mediators of gene networks implicated in the hypoxic response and the switch to glycolysis that occurs in sepsis, including HIF1α and mTOR, and mediators of endotoxin tolerance, T-cell activation, and viral defence. Interpretation Our integrated genomics approach advances understanding of heterogeneity in sepsis by defining subgroups of patients with different immune response states and prognoses, as well as revealing the role of underlying genetic variation. Our findings provide new insights into the pathogenesis of sepsis and create opportunities for a precision medicine approach to enable targeted therapeutic intervention to improve sepsis outcomes. Funding European Commission, Medical Research Council (UK), and the Wellcome Trust.

Extensive characterization of NF-κB binding uncovers non-canonical motifs and advances the interpretation of genetic functional traits

BackgroundGenetic studies have provided ample evidence of the influence of non-coding DNA polymorphisms on trait variance, particularly those occurring within transcription factor binding sites. Protein binding microarrays and other platforms that can map these sites with great precision have enhanced our understanding of how a single nucleotide polymorphism can alter binding potential within an in vitro setting, allowing for greater predictive capability of its effect on a transcription factor binding site.ResultsWe have used protein binding microarrays and electrophoretic mobility shift assay-sequencing (EMSA-Seq), a deep sequencing based method we developed to analyze nine distinct human NF-κB dimers. This family of transcription factors is one of the most extensively studied, but our understanding of its DNA binding preferences has been limited to the originally described consensus motif, GGRRNNYYCC. We highlight differences between NF-κB family members and also put under the spotlight non-canonical motifs that have so far received little attention. We utilize our data to interpret the binding of transcription factors between individuals across 1,405 genomic regions laden with single nucleotide polymorphisms. We also associated binding correlations made using our data with risk alleles of disease and demonstrate its utility as a tool for functional studies of single nucleotide polymorphisms in regulatory regions.ConclusionsNF-κB dimers bind specifically to non-canonical motifs and these can be found within genomic regions in which a canonical motif is not evident. Binding affinity data generated with these different motifs can be used in conjunction with data from chromatin immunoprecipitation-sequencing (ChIP-Seq) to enable allele-specific analyses of expression and transcription factor-DNA interactions on a genome-wide scale.

Choice of transcripts and software has a large effect on variant annotation.

BackgroundVariant annotation is a crucial step in the analysis of genome sequencing data. Functional annotation results can have a strong influence on the ultimate conclusions of disease studies. Incorrect or incomplete annotations can cause researchers both to overlook potentially disease-relevant DNA variants and to dilute interesting variants in a pool of false positives. Researchers are aware of these issues in general, but the extent of the dependency of final results on the choice of transcripts and software used for annotation has not been quantified in detail.MethodsThis paper quantifies the extent of differences in annotation of 80 million variants from a whole-genome sequencing study. We compare results using the RefSeq and Ensembl transcript sets as the basis for variant annotation with the software Annovar, and also compare the results from two annotation software packages, Annovar and VEP (Ensembl’s Variant Effect Predictor), when using Ensembl transcripts.ResultsWe found only 44% agreement in annotations for putative loss-of-function variants when using the RefSeq and Ensembl transcript sets as the basis for annotation with Annovar. The rate of matching annotations for loss-of-function and nonsynonymous variants combined was 79% and for all exonic variants it was 83%. When comparing results from Annovar and VEP using Ensembl transcripts, matching annotations were seen for only 65% of loss-of-function variants and 87% of all exonic variants, with splicing variants revealed as the category with the greatest discrepancy. Using these comparisons, we characterised the types of apparent errors made by Annovar and VEP and discuss their impact on the analysis of DNA variants in genome sequencing studies.ConclusionsVariant annotation is not yet a solved problem. Choice of transcript set can have a large effect on the ultimate variant annotations obtained in a whole-genome sequencing study. Choice of annotation software can also have a substantial effect. The annotation step in the analysis of a genome sequencing study must therefore be considered carefully, and a conscious choice made as to which transcript set and software are used for annotation.

Genomic modulators of gene expression in human neutrophils

Neutrophils form the most abundant leukocyte subset and are central to many disease processes. Technical challenges in transcriptomic profiling have prohibited genomic approaches to date. Here we map expression quantitative trait loci (eQTL) in peripheral blood CD16+ neutrophils from 101 healthy European adults. We identify cis-eQTL for 3281 neutrophil-expressed genes including many implicated in neutrophil function, with 450 of these not previously observed in myeloid or lymphoid cells. Paired comparison with monocyte eQTL demonstrates nuanced conditioning of genetic regulation of gene expression by cellular context, which relates to cell-type-specific DNA methylation and histone modifications. Neutrophil eQTL are markedly enriched for trait-associated variants particularly autoimmune, allergy and infectious disease. We further demonstrate how eQTL in PADI4 and NOD2 delineate risk variant function in rheumatoid arthritis, leprosy and Crohns disease. Taken together, these data help advance understanding of the genetics of gene expression, neutrophil biology and immune-related diseases.

Shared and Distinct Aspects of the Sepsis Transcriptomic Response to Fecal Peritonitis and Pneumonia

&NA; Rationale: Heterogeneity in the septic response has hindered efforts to understand pathophysiology and develop targeted therapies. Source of infection, with different causative organisms and temporal changes, might influence this heterogeneity. Objectives: To investigate individual and temporal variations in the transcriptomic response to sepsis due to fecal peritonitis, and to compare these with the same parameters in community‐acquired pneumonia. Methods: We performed genome‐wide gene expression profiling in peripheral blood leukocytes of adult patients admitted to intensive care with sepsis due to fecal peritonitis (n = 117) or community‐acquired pneumonia (n = 126), and of control subjects without sepsis (n = 10). Measurements and Main Results: A substantial portion of the transcribed genome (18%) was differentially expressed compared with that of control subjects, independent of source of infection, with eukaryotic initiation factor 2 signaling being the most enriched canonical pathway. We identified two sepsis response signature (SRS) subgroups in fecal peritonitis associated with early mortality (P = 0.01; hazard ratio, 4.78). We defined gene sets predictive of SRS group, and serial sampling demonstrated that subgroup membership is dynamic during intensive care unit admission. We found that SRS is the major predictor of transcriptomic variation; a small number of genes (n = 263) were differentially regulated according to the source of infection, enriched for IFN signaling and antigen presentation. We define temporal changes in gene expression from disease onset involving phagosome formation as well as natural killer cell and IL‐3 signaling. Conclusions: The majority of the sepsis transcriptomic response is independent of the source of infection and includes signatures reflecting immune response state and prognosis. A modest number of genes show evidence of specificity. Our findings highlight opportunities for patient stratification and precision medicine in sepsis.

Genomic mapping of the MHC transactivator CIITA using an integrated ChIP-seq and genetical genomics approach

BackgroundThe master transactivator CIITA is essential to the regulation of Major Histocompatibility Complex (MHC) class II genes and an effective immune response. CIITA is known to modulate a small number of non-MHC genes involved in antigen presentation such as CD74 and B2M but its broader genome-wide function and relationship with underlying genetic diversity has not been resolved.ResultsWe report the first genome-wide ChIP-seq map for CIITA and complement this by mapping inter-individual variation in CIITA expression as a quantitative trait. We analyse CIITA recruitment for pathophysiologically relevant primary human B cells and monocytes, resting and treated with interferon-gamma, in the context of the epigenomic regulatory landscape and DNA-binding proteins associated with the CIITA enhanceosome including RFX, CREB1/ATF1 and NFY. We confirm recruitment to proximal promoter sequences in MHC class II genes and more distally involving the canonical CIITA enhanceosome. Overall, we map 843 CIITA binding intervals involving 442 genes and find 95% of intervals are located outside the MHC and 60% not associated with RFX5 binding. Binding intervals are enriched for genes involved in immune function and infectious disease with novel loci including major histone gene clusters. We resolve differentially expressed genes associated in trans with a CIITA intronic sequence variant, integrate with CIITA recruitment and show how this is mediated by allele-specific recruitment of NF-kB.ConclusionsOur results indicate a broader role for CIITA beyond the MHC involving immune-related genes. We provide new insights into allele-specific regulation of CIITA informative for understanding gene function and disease.

High resolution HLA haplotyping by imputation for a British population bioresource

This study aimed to establish the occurrence and frequency of HLA alleles and haplotypes for a healthy British Caucasian population bioresource from Oxfordshire. We present the results of imputation from HLA SNP genotyping data using SNP2HLA for 5553 individuals from Oxford Biobank, defining one- and two-field alleles together with amino acid polymorphisms. We show that this achieves a high level of accuracy with validation using sequence-specific primer amplification PCR. We define six- and eight-locus HLA haplotypes for this population by Bayesian methods implemented using PHASE. We determine patterns of linkage disequilibrium and recombination for these individuals involving classical HLA loci and show how analysis within a haplotype block structure may be more tractable for imputed data. Our findings contribute to knowledge of HLA diversity in healthy populations and further validate future large-scale use of HLA imputation as an informative approach in population bioresources.