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Understanding how human genetics influence infectious disease susceptibility offers the opportunity for new insights into pathogenesis, potential drug targets, risk stratification, response to therapy and vaccination. As new infectious diseases continue to emerge, together with growing levels of antimicrobial resistance and an increasing awareness of substantial differences between populations in genetic associations, the need for such work is expanding. In this Review, we illustrate how our understanding of the host–pathogen relationship is advancing through holistic approaches, describing current strategies to investigate the role of host genetic variation in established and emerging infections, including COVID-19, the need for wider application to diverse global populations mirroring the burden of disease, the impact of pathogen and vector genetic diversity and a broad array of immune and inflammation phenotypes that can be mapped as traits in health and disease. Insights from study of inborn errors of immunity and multi-omics profiling together with developments in analytical methods are further advancing our knowledge of this important area.Infectious diseases are an ever-present global threat. In this Review, Kwok, Mentzer and Knight discuss our latest understanding of how human genetics influence susceptibility to disease. Furthermore, they discuss emerging progress in the interplay between host and pathogen genetics, molecular responses to infection and vaccination, and opportunities to bring these aspects together for rapid responses to emerging diseases such as COVID-19.

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.

The severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) disease (COVID-19) pandemic has caused millions of deaths worldwide. Genome-wide association studies identified the 3p21.31 region as conferring a twofold increased risk of respiratory failure. Here, using a combined multiomics and machine learning approach, we identify the gain-of-function risk A allele of an SNP, rs17713054G>A, as a probable causative variant. We show with chromosome conformation capture and gene-expression analysis that the rs17713054-affected enhancer upregulates the interacting gene, leucine zipper transcription factor like 1 ( LZTFL1 ). Selective spatial transcriptomic analysis of lung biopsies from patients with COVID-19 shows the presence of signals associated with epithelial–mesenchymal transition (EMT), a viral response pathway that is regulated by LZTFL1 . We conclude that pulmonary epithelial cells undergoing EMT, rather than immune cells, are likely responsible for the 3p21.31-associated risk. Since the 3p21.31 effect is conferred by a gain-of-function, LZTFL1 may represent a therapeutic target. SNP rs17713054 in the 3p21.31 COVID-19 risk locus is identified as a probable causative variant for disease association. Chromatin conformation and gene expression data indicate that LZTFL1 is impacted by rs17713054 in pulmonary epithelial cells.

Background Biological interpretation of genomic summary data such as those resulting from genome-wide association studies (GWAS) and expression quantitative trait loci (eQTL) studies is one of the major bottlenecks in medical genomics research, calling for efficient and integrative tools to resolve this problem. Results We introduce eXploring Genomic Relations (XGR), an open source tool designed for enhanced interpretation of genomic summary data enabling downstream knowledge discovery. Targeting users of varying computational skills, XGR utilises prior biological knowledge and relationships in a highly integrated but easily accessible way to make user-input genomic summary datasets more interpretable. We show how by incorporating ontology, annotation, and systems biology network-driven approaches, XGR generates more informative results than conventional analyses. We apply XGR to GWAS and eQTL summary data to explore the genomic landscape of the activated innate immune response and common immunological diseases. We provide genomic evidence for a disease taxonomy supporting the concept of a disease spectrum from autoimmune to autoinflammatory disorders. We also show how XGR can define SNP-modulated gene networks and pathways that are shared and distinct between diseases, how it achieves functional, phenotypic and epigenomic annotations of genes and variants, and how it enables exploring annotation-based relationships between genetic variants. Conclusions XGR provides a single integrated solution to enhance interpretation of genomic summary data for downstream biological discovery. XGR is released as both an R package and a web-app, freely available at http://galahad.well.ox.ac.uk/XGR .

Lude Franke and colleagues report the results of a large expression QTL study performed on peripheral blood samples from 5,311 individuals. They identify trans -eQTL effects for 103 independent loci that were previously associated with complex traits at genome-wide significance, suggesting that this approach can provide insights into the downstream effects of many trait-associated variants. Identifying the downstream effects of disease-associated SNPs is challenging. To help overcome this problem, we performed expression quantitative trait locus (eQTL) meta-analysis in non-transformed peripheral blood samples from 5,311 individuals with replication in 2,775 individuals. We identified and replicated trans eQTLs for 233 SNPs (reflecting 103 independent loci) that were previously associated with complex traits at genome-wide significance. Some of these SNPs affect multiple genes in trans that are known to be altered in individuals with disease: rs4917014, previously associated with systemic lupus erythematosus (SLE) 1 , altered gene expression of C1QB and five type I interferon response genes, both hallmarks of SLE 2 , 3 , 4 . DeepSAGE RNA sequencing showed that rs4917014 strongly alters the 3′ UTR levels of IKZF1 in cis , and chromatin immunoprecipitation and sequencing analysis of the trans -regulated genes implicated IKZF1 as the causal gene. Variants associated with cholesterol metabolism and type 1 diabetes showed similar phenomena, indicating that large-scale eQTL mapping provides insight into the downstream effects of many trait-associated variants.

Multiple sclerosis (MS) is a complex trait in which allelic variation in the MHC class II region exerts the single strongest effect on genetic risk. Epidemiological data in MS provide strong evidence that environmental factors act at a population level to influence the unusual geographical distribution of this disease. Growing evidence implicates sunlight or vitamin D as a key environmental factor in aetiology. We hypothesised that this environmental candidate might interact with inherited factors and sought responsive regulatory elements in the MHC class II region. Sequence analysis localised a single MHC vitamin D response element (VDRE) to the promoter region of HLA-DRB1. Sequencing of this promoter in greater than 1,000 chromosomes from HLA-DRB1 homozygotes showed absolute conservation of this putative VDRE on HLA-DRB1*15 haplotypes. In contrast, there was striking variation among non-MS-associated haplotypes. Electrophoretic mobility shift assays showed specific recruitment of vitamin D receptor to the VDRE in the HLA-DRB1*15 promoter, confirmed by chromatin immunoprecipitation experiments using lymphoblastoid cells homozygous for HLA-DRB1*15. Transient transfection using a luciferase reporter assay showed a functional role for this VDRE. B cells transiently transfected with the HLA-DRB1*15 gene promoter showed increased expression on stimulation with 1,25-dihydroxyvitamin D3 (P = 0.002) that was lost both on deletion of the VDRE or with the homologous \"VDRE\" sequence found in non-MS-associated HLA-DRB1 haplotypes. Flow cytometric analysis showed a specific increase in the cell surface expression of HLA-DRB1 upon addition of vitamin D only in HLA-DRB1*15 bearing lymphoblastoid cells. This study further implicates vitamin D as a strong environmental candidate in MS by demonstrating direct functional interaction with the major locus determining genetic susceptibility. These findings support a connection between the main epidemiological and genetic features of this disease with major practical implications for studies of disease mechanism and prevention.

Inappropriate activation or inadequate regulation of CD4+ and CD8+ T cells may contribute to the initiation and progression of multiple autoimmune and inflammatory diseases. Studies on disease-associated genetic polymorphisms have highlighted the importance of biological context for many regulatory variants, which is particularly relevant in understanding the genetic regulation of the immune system and its cellular phenotypes. Here we show cell type-specific regulation of transcript levels of genes associated with several autoimmune diseases in CD4+ and CD8+ T cells including a trans-acting regulatory locus at chr12q13.2 containing the rs1131017 SNP in the RPS26 gene. Most remarkably, we identify a common missense variant in IL27, associated with type 1 diabetes that results in decreased functional activity of the protein and reduced expression levels of downstream IRF1 and STAT1 in CD4+ T cells only. Altogether, our results indicate that eQTL mapping in purified T cells provides novel functional insights into polymorphisms and pathways associated with autoimmune diseases.

Background The immune response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in COVID-19 patients has been extensively investigated. However, much less is known about the long-term effects of infection in patients and how it could affect the immune system and its capacity to respond to future perturbations. Methods Using a targeted single-cell multiomics approach, we have recently identified a prolonged anti-inflammatory gene expression signature in T and NK cells in type 1 diabetes patients treated with low-dose IL-2. Here, we investigated the dynamics of this signature in three independent cohorts of COVID-19 patients: (i) the Oxford COVID-19 Multi-omics Blood Atlas (COMBAT) dataset, a cross-sectional cohort including 77 COVID-19 patients and ten healthy donors; (ii) the INCOV dataset, consisting of 525 samples taken from 209 COVID-19 patients during and after infection; and (iii) a longitudinal dataset consisting of 269 whole-blood samples taken from 139 COVID-19 patients followed for a period of up to 7 months after the onset of symptoms using a bulk transcriptomic approach. Results We discovered that SARS-CoV-2 infection leads to a prolonged alteration of the gene expression profile of circulating T, B and NK cells and monocytes. Some of the genes affected were the same as those present in the IL-2-induced anti-inflammatory gene expression signature but were regulated in the opposite direction, implying a pro-inflammatory status. The altered transcriptional profile was detected in COVID-19 patients for at least 2 months after the onset of the disease symptoms but was not observed in response to influenza infection or sepsis. Gene network analysis suggested a central role for the transcriptional factor NF-κB in the regulation of the observed transcriptional alterations. Conclusions SARS-CoV-2 infection causes a prolonged increase in the pro-inflammatory transcriptional status that could predispose post-acute patients to the development of long-term health consequences, including autoimmune disease, reactivation of other viruses and disruption of the host immune system-microbiome ecosystem.

Background Chromatin states and enhancers associate gene expression, cell identity and disease. Here, we systematically delineate the acute innate immune response to endotoxin in terms of human macrophage enhancer activity and contrast with endotoxin tolerance, profiling the coding and non-coding transcriptome, chromatin accessibility and epigenetic modifications. Results We describe the spectrum of enhancers under acute and tolerance conditions and the regulatory networks between these enhancers and biological processes including gene expression, splicing regulation, transcription factor binding and enhancer RNA signatures. We demonstrate that the vast majority of differentially regulated enhancers on acute stimulation are subject to tolerance and that expression quantitative trait loci, disease-risk variants and eRNAs are enriched in these regulatory regions and related to context-specific gene expression. We find enrichment for context-specific eQTL involving endotoxin response and specific infections and delineate specific differential regions informative for GWAS variants in inflammatory bowel disease and multiple sclerosis, together with a context-specific enhancer involving a bacterial infection eQTL for KLF4 . We show enrichment in differential enhancers for tolerance involving transcription factors NFκB-p65, STATs and IRFs and prioritize putative causal genes directly linking genetic variants and disease risk enhancers. We further delineate similarities and differences in epigenetic landscape between stem cell-derived macrophages and primary cells and characterize the context-specific enhancer activities for key innate immune response genes KLF4 , SLAMF1 and IL2RA . Conclusions Our study demonstrates the importance of context-specific macrophage enhancers in gene regulation and utility for interpreting disease associations, providing a roadmap to link genetic variants with molecular and cellular functions.

Insights into variation in monocyte context-specific splicing and transcript usage are limited. Here, we perform paired gene and transcript QTL mapping across distinct immune states using RNA sequencing data of monocytes isolated from a cohort of 185 healthy Europeans incubated alone or in the presence of interferon gamma (IFN-γ) or lipopolysaccharide (LPS). We identify regulatory variants for 5749 genes and 8727 transcripts, with 291 context-specific transcript QTL colocalizing with GWAS loci. Notable disease relevant associations include IFN-γ specific transcript QTL at COVID-19 severity locus rs10735079, where allelic variation modulates context-specific splicing of OAS1 , and at rs4072037, a risk allele for gastro-esophageal cancer, which associates with context-specific splicing of MUC1 . We use DNA methylation data from the same cells to demonstrate overlap between methylation QTL and causal context-specific expression QTL, permitting inference of the direction of effect. Finally, we identify a subset of expression QTL that uncouple genes from proximally acting regulatory networks, creating ‘co-expression QTL’ with different allele-specific correlation networks. Our findings highlight the interplay between context and genetics in the regulation of the monocyte gene expression and splicing, revealing putative mechanisms of diverse disease risk alleles including for COVID-19 and cancer. Our understanding of variation in monocyte context-specific splicing and transcript usage is limited. Here, the authors find genetic variants that affect gene splicing in monocytes in specific contexts, including several diseases, and in response to stimulants.