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

The single-cell eQTLGen consortium

In recent years, functional genomics approaches combining genetic information with bulk RNA-sequencing data have identified the downstream expression effects of disease-associated genetic risk factors through so-called expression quantitative trait locus (eQTL) analysis. Single-cell RNA-sequencing creates enormous opportunities for mapping eQTLs across different cell types and in dynamic processes, many of which are obscured when using bulk methods. Rapid increase in throughput and reduction in cost per cell now allow this technology to be applied to large-scale population genetics studies. To fully leverage these emerging data resources, we have founded the single-cell eQTLGen consortium (sc-eQTLGen), aimed at pinpointing the cellular contexts in which disease-causing genetic variants affect gene expression. Here, we outline the goals, approach and potential utility of the sc-eQTLGen consortium. We also provide a set of study design considerations for future single-cell eQTL studies.

Gene expression changes in lymphoblastoid cell lines and primary B cells by dexamethasone

BACKGROUND

Human Epstein-Barr virus-transformed lymphoblastoid cell lines (LCLs) have been thought to be a useful model system for pharmacogenomics studies. The purpose of this study was to determine the effect of Epstein-Barr virus transformation on gene expression changes by dexamethasone (Dex) in LCLs and primary B cells (PBCs) derived from the same individuals.

PATIENTS AND METHODS

We prepared LCLs and purified PBCs from the same six male donors participating in the Childhood Asthma Management Program clinical trial, and compared mRNA profiles after 6 h incubation with Dex (10 mol/l) or sham buffer. We assessed differential expression and put the list of differentially expressed genes into the web interface of ConsensusPathDB to find the pathway-level interpretation of our genes specified. As a supplementary analysis, we looked at the expression of the Dex-regulated (inducing or repressing) genes in treatment-naive PBCs and LCLs (pre-Dex treatment) from the GSE30916 dataset.

RESULTS

By hierarchical clustering, we found clustering of probes by cell types but not by individuals irrespective of Dex treatment. We observed that the Dex-regulated genes significantly overlapped in PBCs and LCLs. In addition, the expression of these genes showed significant correlations between treatment-naive PBCs and LCLs. Common genes showing significantly decreased expressions by the Dex treatment in both cells were enriched in immune responses and proinflammatory signaling pathways.

CONCLUSION

Taken together, these results suggest the uses of LCLs are representative of the primary biologic effects of corticosteroids treatment.

Quantitative genetic analysis deciphers the impact of cis and trans regulation on cell-to-cell variability in protein expression levels

Identifying the factors that shape protein expression variability in complex multi-cellular organisms has primarily focused on promoter architecture and regulation of single-cell expression in cis. However, this targeted approach has to date been unable to identify major regulators of cell-to-cell gene expression variability in humans. To address this, we have combined single-cell protein expression measurements in the human immune system using flow cytometry with a quantitative genetics analysis. For the majority of proteins whose variability in expression has a heritable component, we find that genetic variants act in trans, with notably fewer variants acting in cis. Furthermore, we highlight using Mendelian Randomization that these variability-Quantitative Trait Loci might be driven by the cis regulation of upstream genes. This indicates that natural selection may balance the impact of gene regulation in cis with downstream impacts on expression variability in trans.

Ancestry-Specific Analyses Reveal Differential Demographic Histories and Opposite Selective Pressures in Modern South Asian Populations

Genetic variation in contemporary South Asian populations follows a northwest to southeast decreasing cline of shared West Eurasian ancestry. A growing body of ancient DNA evidence is being used to build increasingly more realistic models of demographic changes in the last few thousand years. Through high-quality modern genomes, these models can be tested for gene and genome level deviations. Using local ancestry deconvolution and masking, we reconstructed population-specific surrogates of the two main ancestral components for more than 500 samples from 25 South Asian populations and showed our approach to be robust via coalescent simulations.

Our f3 and f4 statistics–based estimates reveal that the reconstructed haplotypes are good proxies for the source populations that admixed in the area and point to complex interpopulation relationships within the West Eurasian component, compatible with multiple waves of arrival, as opposed to a simpler one wave scenario. Our approach also provides reliable local haplotypes for future downstream analyses. As one such example, the local ancestry deconvolution in South Asians reveals opposite selective pressures on two pigmentation genes (SLC45A2 and SLC24A5) that are common or fixed in West Eurasians, suggesting post-admixture purifying and positive selection signals, respectively.

cis-regulatory variation modulates susceptibility to enteric infection in the Drosophila genetic reference panel

BACKGROUND

Resistance to enteric pathogens is a complex trait at the crossroads of multiple biological processes. We have previously shown in the Drosophila Genetic Reference Panel (DGRP) that resistance to infection is highly heritable, but our understanding of how the effects of genetic variants affect different molecular mechanisms to determine gut immunocompetence is still limited.

RESULTS

To address this, we perform a systems genetics analysis of the gut transcriptomes from 38 DGRP lines that were orally infected with Pseudomonas entomophila. We identify a large number of condition-specific, expression quantitative trait loci (local-eQTLs) with infection-specific ones located in regions enriched for FOX transcription factor motifs. By assessing the allelic imbalance in the transcriptomes of 19 F1 hybrid lines from a large round robin design, we independently attribute a robust cis-regulatory effect to only 10% of these detected local-eQTLs. However, additional analyses indicate that many local-eQTLs may act in trans instead. Comparison of the transcriptomes of DGRP lines that were either susceptible or resistant to Pseudomonas entomophila infection reveals nutcracker as the only differentially expressed gene. Interestingly, we find that nutcracker is linked to infection-specific eQTLs that correlate with its expression level and to enteric infection susceptibility. Further regulatory analysis reveals one particular eQTL that significantly decreases the binding affinity for the repressor Broad, driving differential allele-specific nutcracker expression.

CONCLUSIONS

Our collective findings point to a large number of infection-specific cis- and trans-acting eQTLs in the DGRP, including one common non-coding variant that lowers enteric infection susceptibility.

MHC Class II (DRB) Promoter Polymorphism and Its Role in Parasite Control among Malaria Patients

MHC class II (MHCII) molecules are cell surface glycoproteins that play an important role to develop adaptive immune responses. MHCII-disease association is not restricted to structural variation alone but also may extend to genetic variations, which may modulate gene expression. The observed variations in class II gene expression make it possible that the association of MHCII polymorphism with diseases may relate to the level of gene expression in addition to the restriction of response to Ag. Understanding the extent of, and the mechanisms underlying, transcription factor DNA binding variation is therefore key to elucidate the molecular determinants of complex phenotypes. In this study, we investigated whether single nucleotide polymorphisms in MHCII-DRB regulatory gene may be associated with clinical outcomes of malaria in Plasmodium-infected individuals. To this end, we conducted a case-control study to compare patients who had mild malaria with those patients who had asymptomatic Plasmodium infection. It demonstrates that GTAT haplotype exerts an increased DRB transcriptional activity, resulting in higher DRB expression and subsequently perturbed Ag presentation and T cell activation, higher TLR-mediated innate immune gene expression, and Ag clearance, so low parasitemia in comparison with haplotypes other than GTAT (GTAC, GGGT). Hence, we hypothesized that DRB gene promoter polymorphism might lead to altered DRB gene expression, which could possibly affect the TLR-triggered innate immune responses in malaria patients. These genetic findings may contribute to the understanding of the pathogenesis of malaria and will facilitate the rational vaccine design for malaria.

Exploratory analysis of genetic variants influencing molecular traits in cerebral cortex of suicide completers

Genetic factors have been implicated in suicidal behavior. It has been suggested that one of the roles of genetic factors in suicide could be represented by the effect of genetic variants on gene expression regulation. Alteration in the expression of genes participating in multiple biological systems in the suicidal brain has been demonstrated, so it is imperative to identify genetic variants that could influence gene expression or its regulatory mechanisms. In this study, we integrated DNA methylation, gene expression, and genotype data from the prefrontal cortex of suicides to identify genetic variants that could be factors in the regulation of gene expression, generally called quantitative trait locus (xQTLs). We identify 6,224 methylation quantitative trait loci and 2,239 expression quantitative trait loci (eQTLs) in the prefrontal cortex of suicide completers. The xQTLs identified influence the expression of genes involved in neurodevelopment and cell organization. Two of the eQTLs identified (rs8065311 and rs1019238) were previously associated with cannabis dependence, highlighting a candidate genetic variant for the increased suicide risk in subjects with substance use disorders. Our findings suggest that genetic variants may regulate gene expression in the prefrontal cortex of suicides through the modulation of promoter and enhancer activity, and to a lesser extent, binding transcription factors.

From genome-wide association studies to rational drug target prioritisation in inflammatory arthritis

Early identification of genetically validated drug targets can increase the chances of successful late-stage drug development. 81 high-quality genome-wide association studies (GWAS) in diseases related to inflammatory arthritis have been curated into the GWAS catalogue; however, translation of genetic findings from GWAS into rational drug target discovery has been poor. No human genetic findings have completely driven drug development for inflammatory arthritis; however, genetic associations have partly driven the development of abatacept (CTLA-4-Ig) in rheumatoid arthritis and secukinumab (anti-IL-23R) in ankylosing spondylitis. Roadblocks to progress exist, including little knowledge of the genetic architecture and regulatory mechanisms underlying associations, and the need to identify gene regulatory networks and assess target tractability. New opportunities are arising that could maximise the informativeness of GWAS for drug target validation. Genetic variants can be linked to core genes by using functional genomics and then to peripheral genes interconnected to core genes using network information. Moreover, identification of crosstalk between biological pathways might highlight key points for therapeutic intervention.

Multivariate Genome-wide Association Analysis of a Cytokine Network Reveals Variants with Widespread Immune, Haematological, and Cardiometabolic Pleiotropy

Cytokines are essential regulatory components of the immune system, and their aberrant levels have been linked to many disease states. Despite increasing evidence that cytokines operate in concert, many of the physiological interactions between cytokines, and the shared genetic architecture that underlies them, remain unknown. Here, we aimed to identify and characterize genetic variants with pleiotropic effects on cytokines. Using three population-based cohorts (n = 9,263), we performed multivariate genome-wide association studies (GWAS) for a correlation network of 11 circulating cytokines, then combined our results in meta-analysis. We identified a total of eight loci significantly associated with the cytokine network, of which two (PDGFRB and ABO) had not been detected previously. In addition, conditional analyses revealed a further four secondary signals at three known cytokine loci. Integration, through the use of Bayesian colocalization analysis, of publicly available GWAS summary statistics with the cytokine network associations revealed shared causal variants between the eight cytokine loci and other traits; in particular, cytokine network variants at the ABO, SERPINE2, and ZFPM2 loci showed pleiotropic effects on the production of immune-related proteins, on metabolic traits such as lipoprotein and lipid levels, on blood-cell-related traits such as platelet count, and on disease traits such as coronary artery disease and type 2 diabetes.

Advances in genetics toward identifying pathogenic cell states of rheumatoid arthritis

Rheumatoid arthritis (RA) risk has a large genetic component (~60%) that is still not fully understood. This has hampered the design of effective treatments that could promise lifelong remission. RA is a polygenic disease with 106 known genome-wide significant associated loci and thousands of small effect causal variants. Our current understanding of RA risk has suggested cell-type-specific contexts for causal variants, implicating CD4 + effector memory T cells, as well as monocytes, B cells and stromal fibroblasts. While these cellular states and categories are still mechanistically broad, future studies may identify causal cell subpopulations. These efforts are propelled by advances in single cell profiling. Identification of causal cell subpopulations may accelerate therapeutic intervention to achieve lifelong remission.

DNA variants affecting the expression of numerous genes in trans have diverse mechanisms of action and evolutionary histories

DNA variants that alter gene expression contribute to variation in many phenotypic traits. In particular, trans-acting variants, which are often located on different chromosomes from the genes they affect, are an important source of heritable gene expression variation. However, our knowledge about the identity and mechanism of causal trans-acting variants remains limited. Here, we developed a fine-mapping strategy called CRISPR-Swap and dissected three expression quantitative trait locus (eQTL) hotspots known to alter the expression of numerous genes in trans in the yeast Saccharomyces cerevisiae. Causal variants were identified by engineering recombinant alleles and quantifying the effects of these alleles on the expression of a green fluorescent protein-tagged gene affected by the given locus in trans. We validated the effect of each variant on the expression of multiple genes by RNA-sequencing. The three variants differed in their molecular mechanism, the type of genes they reside in, and their distribution in natural populations. While a missense leucine-to-serine variant at position 63 in the transcription factor Oaf1 (L63S) was almost exclusively present in the reference laboratory strain, the two other variants were frequent among S. cerevisiae isolates. A causal missense variant in the glucose receptor Rgt2 (V539I) occurred at a poorly conserved amino acid residue and its effect was strongly dependent on the concentration of glucose in the culture medium. A noncoding variant in the conserved fatty acid regulated (FAR) element of the OLE1 promoter influenced the expression of the fatty acid desaturase Ole1 in cis and, by modulating the level of this essential enzyme, other genes in trans. The OAF1 and OLE1 variants showed a non-additive genetic interaction, and affected cellular lipid metabolism. These results demonstrate that the molecular basis of trans-regulatory variation is diverse, highlighting the challenges in predicting which natural genetic variants affect gene expression.

Differences in the DNA sequence of individual genomes contribute to differences in many traits, such as appearance, physiology, and the risk for common diseases. An important group of these DNA variants influences how individual genes across the genome are turned on or off. In this paper, we describe a strategy for identifying such “trans-acting” variants in different strains of baker’s yeast. We used this strategy to reveal three single DNA base changes that each influences the expression of dozens of genes. These three DNA variants were very different from each other. Two of them changed the protein sequence, one in a transcription factor and the other in a sugar sensor. The third changed the expression of an enzyme, a change that in turn caused other genes to alter their expression. One variant existed in only a few yeast isolates, while the other two existed in many isolates collected from around the world. This diversity of DNA variants that influence the expression of many other genes illustrates how difficult it is to predict which DNA variants in an individual’s genome will have effects on the organism.

Macrophages in Atherosclerosis Regression

Macrophages play a central role in the development of atherosclerotic cardiovascular disease (ASCVD), which encompasses coronary artery disease, peripheral artery disease, cerebrovascular disease, and aortic atherosclerosis. In each vascular bed, macrophages contribute to the maintenance of the local inflammatory response, propagate plaque development, and promote thrombosis. These central roles, coupled with their plasticity, makes macrophages attractive therapeutic targets in stemming the development of and stabilizing existing atherosclerosis. In the context of ASCVD, classically activated M1 macrophages initiate and sustain inflammation, and alternatively activated M2 macrophages resolve inflammation. However, this classification is now considered an oversimplification, and a greater understanding of plaque macrophage physiology in ASCVD is required to aid in the development of therapeutics to promote ASCVD regression. Reviewed herein are the macrophage phenotypes and molecular regulators characteristic of ASCVD regression, and the current murine models of ASCVD regression.

Protecting Tumors by Preventing Human Papilloma Virus Antigen Presentation: Insights from Emerging Bioinformatics Algorithms

Recent developments in bioinformatics technologies have led to advances in our understanding of how oncogenic viruses such as the human papilloma virus drive cancer progression and evade the host immune system. Here, we focus our review on understanding how these emerging bioinformatics technologies influence our understanding of how human papilloma virus (HPV) drives immune escape in cancers of the head and neck, and how these new informatics approaches may be generally applicable to other virally driven cancers. Indeed, these tools enable researchers to put existing data from genome wide association studies, in which high risk alleles have been identified, in the context of our current understanding of cellular processes regulating neoantigen presentation. In the future, these new bioinformatics approaches are highly likely to influence precision medicine-based decision making for the use of immunotherapies in virally driven cancers.

A CARD9 single-nucleotide polymorphism rs4077515 is associated with reduced susceptibility to and severity of primary immune thrombocytopenia

Primary immune thrombocytopenia (ITP) is an acquired autoimmune disease characterized by a low platelet count and consequent increased risk of bleeding. The etiology underlying this condition remains poorly understood. The aim of this study is to evaluate the association of a single nucleotide polymorphism (SNP) rs4077515 in the caspase recruitment domain-containing protein 9 (CARD9) gene with the pathogenesis and therapy of ITP. Two hundred ninety-four patients with ITP and 324 age-matched healthy participants were recruited in this case-control study. Genotyping of CARD9 rs4077515 polymorphism was performed by Sanger sequencing. Our results revealed that a polymorphism rs4077515 in CARD9 gene is associated with decreased risk of susceptibility to and severity of ITP (susceptibility: codominant, AA vs. GG, OR = 0.175, 95% CI = 0.054-0.776, p = 0.001; recessive, GG + AG vs. AA, OR = 6.183, 95% CI = 2.287-16.715, p < 0.001; severity: allele, A vs. G, OR = 0.685, 95% CI = 0.476-0.985, p = 0.041; codominant, AG vs. GG, OR = 0.571, 95% CI = 0.350-0.931, p = 0.025; dominant, AA + AG vs. GG, OR = 0.558, 95% CI = 0.343-0.907, p = 0.019). The existence of the allele A, the mutant AA genotype and the heterozygous AG genotype of CARD9 rs4077515, plays a protective role in ITP. However, CARD9 rs4077515 polymorphism had no effect on corticosteroid sensitivity or refractoriness of ITP.

Variants in oxidative stress-related genes affect the chemosensitivity through Nrf2-mediated signaling pathway in biliary tract cancer

BACKGROUND

Oxidative stress and their effectors play critical roles in carcinogenesis and chemoresistance. However, the role of oxidative stress-related genes variants in biliary tract cancer (BTC) chemoresistance remains unknown. In this work, we aim to investigate oxidative stress-dependent molecular mechanisms underlying chemoresistance, and find potential biomarkers to predict chemotherapy response for BTC.

METHODS

Sixty-six SNPs in 21 oxidative stress-related genes were genotyped and analyzed in 367 BTC patients. Immunoblot, immunohistochemical, immunofluorescent, quantitative PCR, chromatin immunoprecipitation analysis and study of animal xenograft models were performed to discover oxidative stress-related susceptibility genes underlying chemoresistance mechanism of BTC.

FINDINGS

We found that 3 functional polymorphisms (CAT_rs769217, GPX4_rs4807542, and GSR_rs3779647), which were shown to affect their respective gene expression levels, modified the effect of chemotherapy on overall survival (OS). We then demonstrated that knockdown of GPX4, CAT, or GSR induced chemoresistance through elevation of ROS level and activation of Nrf2-ABCG2 pathway in BTC cell lines. Moreover, the association between Nrf2 expression and BTC prognosis is only found in patients who received chemotherapy. Knockdown of Nrf2 enhanced chemosensitivity or even eliminated postoperative recurrence in BTC xenograft mouse models. Importantly, upon chemotherapy treatment patients harboring high oxidative stress-related score received higher survival benefit from adjuvant chemotherapy compared with patients with low oxidative stress-related score.

INTERPRETATION

The result of our study suggests, for the first time, that the oxidative stress-related score calculated by combining variations in CAT, GPX4, and GSR or Nrf2 expression could be used for predicting the chemosensitivity of BTC patients. FUND: This work was supported by the National Science Foundation of China, Foundation of Shanghai Shen Kang Hospital Development Center, and Shanghai Outstanding Academic Leaders Plan.

Genetic association of molecular traits: A help to identify causative variants in complex diseases

In the past 15 years, major progresses have been made in the understanding of the genetic basis of regulation of gene expression. These new insights have revolutionized our approach to resolve the genetic variation underlying complex diseases. Gene transcript levels were the first expression phenotypes that were studied. They are heritable and therefore amenable to genome-wide association studies. The genetic variants that modulate them are called expression quantitative trait loci. Their study has been extended to other molecular quantitative trait loci (molQTLs) that regulate gene expression at the various levels, from chromatin state to cellular responses. Altogether, these studies have generated a wealth of basic information on the genome-wide patterns of gene expression and their inter-individual variation. Most importantly, molQTLs have become an invaluable asset in the genetic study of complex diseases. Although the identification of the disease-causing variants on the basis of their overlap with molQTLs requires caution, molQTLs can help to prioritize the relevant candidate gene(s) in the disease-associated regions and bring a functional interpretation of the associated variants, therefore, bridging the gap between genotypes and clinical phenotypes.

Using Transcriptomic Hidden Variables to Infer Context-Specific Genotype Effects in the Brain

Deciphering the environmental contexts at which genetic effects are most prominent is central for making full use of GWAS results in follow-up experiment design and treatment development. However, measuring a large number of environmental factors at high granularity might not always be feasible. Instead, here we propose extracting cellular embedding of environmental factors from gene expression data by using latent variable (LV) analysis and taking these LVs as environmental proxies in detecting gene-by-environment (GxE) interaction effects on gene expression, i.e., GxE expression quantitative trait loci (eQTLs). Applying this approach to two largest brain eQTL datasets (n = 1,100), we show that LVs and GxE eQTLs in one dataset replicate well in the other dataset. Combining the two samples via meta-analysis, 895 GxE eQTLs are identified. On average, GxE effect explains an additional ∼4% variation in expression of each gene that displays a GxE effect. Ten of these 52 genes are associated with cell-type-specific eQTLs, and the remaining genes are multi-functional. Furthermore, after substituting LVs with expression of transcription factors (TF), we found 91 TF-specific eQTLs, which demonstrates an important use of our brain GxE eQTLs.

Genetic Identification of Two Novel Loci Associated with Steroid-Sensitive Nephrotic Syndrome

BACKGROUND

Steroid-sensitive nephrotic syndrome (SSNS), the most common form of nephrotic syndrome in childhood, is considered an autoimmune disease with an established classic HLA association. However, the precise etiology of the disease is unclear. In other autoimmune diseases, the identification of loci outside the classic HLA region by genome-wide association studies (GWAS) has provided critical insights into disease pathogenesis. Previously conducted GWAS of SSNS have not identified non-HLA loci achieving genome-wide significance.

METHODS

In an attempt to identify additional loci associated with SSNS, we conducted a GWAS of a large cohort of European ancestry comprising 422 ethnically homogeneous pediatric patients and 5642 ethnically matched controls.

RESULTS

The GWAS found three loci that achieved genome-wide significance, which explain approximately 14% of the genetic risk for SSNS. It confirmed the previously reported association with the HLA-DR/DQ region (lead single-nucleotide polymorphism [SNP] rs9273542, P=1.59×10-43; odds ratio [OR], 3.39; 95% confidence interval [95% CI], 2.86 to 4.03) and identified two additional loci outside the HLA region on chromosomes 4q13.3 and 6q22.1. The latter contains the calcium homeostasis modulator family member 6 gene CALHM6 (previously called FAM26F). CALHM6 is implicated in immune response modulation; the lead SNP (rs2637678, P=1.27×10-17; OR, 0.51; 95% CI, 0.44 to 0.60) exhibits strong expression quantitative trait loci effects, the risk allele being associated with lower lymphocytic expression of CALHM6.

CONCLUSIONS

Because CALHM6 is implicated in regulating the immune response to infection, this may provide an explanation for the typical triggering of SSNS onset by infections. Our results suggest that a genetically conferred risk of immune dysregulation may be a key component in the pathogenesis of SSNS.

A Genome-Wide Functional Genomics Approach Identifies Susceptibility Pathways to Fungal Bloodstream Infection in Humans

BACKGROUND

Candidemia, one of the most common causes of fungal bloodstream infection, leads to mortality rates up to 40% in affected patients. Understanding genetic mechanisms for differential susceptibility to candidemia may aid in designing host-directed therapies.

METHODS

We performed the first genome-wide association study on candidemia, and we integrated these data with variants that affect cytokines in different cellular systems stimulated with Candida albicans.

RESULTS

We observed strong association between candidemia and a variant, rs8028958, that significantly affects the expression levels of PLA2G4B in blood. We found that up to 35% of the susceptibility loci affect in vitro cytokine production in response to Candida. Furthermore, potential causal genes located within these loci are enriched for lipid and arachidonic acid metabolism. Using an independent cohort, we also showed that the numbers of risk alleles at these loci are negatively correlated with reactive oxygen species and interleukin-6 levels in response to Candida. Finally, there was a significant correlation between susceptibility and allelic scores based on 16 independent candidemia-associated single-nucleotide polymorphisms that affect monocyte-derived cytokines, but not with T cell-derived cytokines.

CONCLUSIONS

Our results prioritize the disturbed lipid homeostasis and oxidative stress as potential mechanisms that affect monocyte-derived cytokines to influence susceptibility to candidemia.

Conserved properties of genetic architecture of renal and fat transcriptomes in rat models of insulin resistance

To define renal molecular mechanisms that are affected by permanent hyperglycaemia and might promote phenotypes relevant to diabetic nephropathy, we carried out linkage analysis of genome-wide gene transcription in the kidneys of F2 offspring from the Goto-Kakizaki (GK) rat model of type 2 diabetes and normoglycaemic Brown Norway (BN) rats. We mapped 2526 statistically significant expression quantitative trait loci (eQTLs) in the cross. More than 40% of eQTLs mapped in the close vicinity of the linked transcripts, underlying possible cis-regulatory mechanisms of gene expression. We identified eQTL hotspots on chromosomes 5 and 9 regulating the expression of 80-165 genes, sex or cross direction effects, and enriched metabolic and immunological processes by segregating GK alleles. Comparative analysis with adipose tissue eQTLs in the same cross showed that 496 eQTLs, in addition to the top enriched biological pathways, are conserved in the two tissues. Extensive similarities in eQTLs mapped in the GK rat and in the spontaneously hypertensive rat (SHR) suggest a common aetiology of disease phenotypes common to the two strains, including insulin resistance, which is a prominent pathophysiological feature in both GK rats and SHRs. Our data shed light on shared and tissue-specific molecular mechanisms that might underlie aetiological aspects of insulin resistance in the context of spontaneously occurring hyperglycaemia and hypertension.

Summary: Kidney and fat expression QTL mapping in rat models of spontaneously occurring insulin resistance associated with either diabetes or hypertension reveals conserved gene expression regulation, suggesting shared aetiology of disease phenotypes.

A genetics-led approach defines the drug target landscape of 30 immune-related traits

Most candidate drugs currently fail later-stage clinical trials, largely due to poor prediction of efficacy on early target selection1. Drug targets with genetic support are more likely to be therapeutically valid2,3, but the translational use of genome-scale data such as from genome-wide association studies for drug target discovery in complex diseases remains challenging4-6. Here, we show that integration of functional genomic and immune-related annotations, together with knowledge of network connectivity, maximizes the informativeness of genetics for target validation, defining the target prioritization landscape for 30 immune traits at the gene and pathway level. We demonstrate how our genetics-led drug target prioritization approach (the priority index) successfully identifies current therapeutics, predicts activity in high-throughput cellular screens (including L1000, CRISPR, mutagenesis and patient-derived cell assays), enables prioritization of under-explored targets and allows for determination of target-level trait relationships. The priority index is an open-access, scalable system accelerating early-stage drug target selection for immune-mediated disease.

Interferon inducible X-linked gene CXorf21 may contribute to sexual dimorphism in Systemic Lupus Erythematosus

Systemic lupus erythematosus (SLE) is an autoimmune disease, characterised by increased expression of type I interferon (IFN)-regulated genes and a striking sex imbalance towards females. Through combined genetic, in silico, in vitro, and ex vivo approaches, we define CXorf21, a gene of hitherto unknown function, which escapes X-chromosome inactivation, as a candidate underlying the Xp21.2 SLE association. We demonstrate that CXorf21 is an IFN-response gene and that the sexual dimorphism in expression is magnified by immunological challenge. Fine-mapping reveals a single haplotype as a potential causal cis-eQTL for CXorf21. We propose that expression is amplified through modification of promoter and 3'-UTR chromatin interactions. Finally, we show that the CXORF21 protein colocalises with TLR7, a pathway implicated in SLE pathogenesis. Our study reveals modulation in gene expression affected by the combination of two hallmarks of SLE: CXorf21 expression increases in a both an IFN-inducible and sex-specific manner.

Expression estimation and eQTL mapping for HLA genes with a personalized pipeline

The HLA (Human Leukocyte Antigens) genes are well-documented targets of balancing selection, and variation at these loci is associated with many disease phenotypes. Variation in expression levels also influences disease susceptibility and resistance, but little information exists about the regulation and population-level patterns of expression. This results from the difficulty in mapping short reads originated from these highly polymorphic loci, and in accounting for the existence of several paralogues. We developed a computational pipeline to accurately estimate expression for HLA genes based on RNA-seq, improving both locus-level and allele-level estimates. First, reads are aligned to all known HLA sequences in order to infer HLA genotypes, then quantification of expression is carried out using a personalized index. We use simulations to show that expression estimates obtained in this way are not biased due to divergence from the reference genome. We applied our pipeline to the GEUVADIS dataset, and compared the quantifications to those obtained with reference transcriptome. Although the personalized pipeline recovers more reads, we found that using the reference transcriptome produces estimates similar to the personalized pipeline (r ≥ 0.87) with the exception of HLA-DQA1. We describe the impact of the HLA-personalized approach on downstream analyses for nine classical HLA loci (HLA-A, HLA-C, HLA-B, HLA-DRA, HLA-DRB1, HLA-DQA1, HLA-DQB1, HLA-DPA1, HLA-DPB1). Although the influence of the HLA-personalized approach is modest for eQTL mapping, the p-values and the causality of the eQTLs obtained are better than when the reference transcriptome is used. We investigate how the eQTLs we identified explain variation in expression among lineages of HLA alleles. Finally, we discuss possible causes underlying differences between expression estimates obtained using RNA-seq, antibody-based approaches and qPCR.

Identifying Multi-Omics Causers and Causal Pathways for Complex Traits

The central dogma of molecular biology delineates a unidirectional causal flow, i.e., DNA → RNA → protein → trait. Genome-wide association studies, next-generation sequencing association studies, and their meta-analyses have successfully identified ~12,000 susceptibility genetic variants that are associated with a broad array of human physiological traits. However, such conventional association studies ignore the mediate causers (i.e., RNA, protein) and the unidirectional causal pathway. Such studies may not be ideally powerful; and the genetic variants identified may not necessarily be genuine causal variants. In this article, we model the central dogma by a mediate causal model and analytically prove that the more remote an omics level is from a physiological trait, the smaller the magnitude of their correlation is. Under both random and extreme sampling schemes, we numerically demonstrate that the proteome-trait correlation test is more powerful than the transcriptome-trait correlation test, which in turn is more powerful than the genotype-trait association test. In conclusion, integrating RNA and protein expressions with DNA data and causal inference are necessary to gain a full understanding of how genetic causal variants contribute to phenotype variations.

A genetic variant associated with multiple sclerosis inversely affects the expression of CD58 and microRNA-548ac from the same gene

Genome-wide association studies have identified more than 200 genetic variants to be associated with an increased risk of developing multiple sclerosis (MS). Still, little is known about the causal molecular mechanisms that underlie the genetic contribution to disease susceptibility. In this study, we investigated the role of the single-nucleotide polymorphism (SNP) rs1414273, which is located within the microRNA-548ac stem-loop sequence in the first intron of the CD58 gene. We conducted an expression quantitative trait locus (eQTL) analysis based on public RNA-sequencing and microarray data of blood-derived cells of more than 1000 subjects. Additionally, CD58 transcripts and mature hsa-miR-548ac molecules were measured using real-time PCR in peripheral blood samples of 32 MS patients. Cell culture experiments were performed to evaluate the efficiency of Drosha-mediated stem-loop processing dependent on genotype and to determine the target genes of this underexplored microRNA. Across different global populations and data sets, carriers of the MS risk allele showed reduced CD58 mRNA levels but increased hsa-miR-548ac levels. We provide evidence that the SNP rs1414273 might alter Drosha cleavage activity, thereby provoking partial uncoupling of CD58 gene expression and microRNA-548ac production from the shared primary transcript in immune cells. Moreover, the microRNA was found to regulate genes, which participate in inflammatory processes and in controlling the balance of protein folding and degradation. We thus uncovered new regulatory implications of the MS-associated haplotype of the CD58 gene locus, and we remind that paradoxical findings can be encountered in the analysis of eQTLs upon data aggregation. Our study illustrates that a better understanding of RNA processing events might help to establish the functional nature of genetic variants, which predispose to inflammatory and neurological diseases.

Functional SNPs in the Human Autoimmunity-Associated Locus 17q12-21

Genome-wide association studies (GWASes) revealed several single-nucleotide polymorphisms (SNPs) in the human 17q12-21 locus associated with autoimmune diseases. However, follow-up studies are still needed to identify causative SNPs directly mediating autoimmune risk in the locus. We have chosen six SNPs in high linkage disequilibrium with the GWAS hits that showed the strongest evidence of causality according to association pattern and epigenetic data and assessed their functionality in a local genomic context using luciferase reporter system. We found that rs12946510, rs4795397, rs12709365, and rs8067378 influenced the reporter expression level in leukocytic cell lines. The strongest effect visible in three distinct cell types was observed for rs12946510 that is predicted to alter MEF2A/C and FOXO1 binding sites.

Most chromatin interactions are not in linkage disequilibrium

Chromatin interactions and linkage disequilibrium (LD) are both pairwise measurements between genomic loci that show block patterns along mammalian chromosomes. Their values are generally high for sites that are nearby in the linear genome but abruptly drop across block boundaries. One function of chromatin boundaries is to insulate regulatory domains from one another. Since recombination is depressed within genes and between distal regulatory elements and their promoters, we hypothesized that LD and chromatin contact frequency might be correlated genome-wide with the boundaries of LD blocks and chromatin domains frequently coinciding. To comprehensively address this question, we compared chromatin contacts in 22 cell types to LD across billions of pairs of loci in the human genome. These computationally intensive analyses revealed that there is no concordance between LD and chromatin interactions, even at genomic distances below 25 kilobases (kb) where both tend to be high. At genomic distances where LD is approximately zero, chromatin interactions are frequent. While LD is somewhat elevated between distal regulatory elements and their promoters, LD block boundaries are depleted—not enriched—at chromatin boundaries. Finally, gene expression and ontology data suggest that chromatin contacts identify regulatory variants more reliably than do LD and genomic proximity. We conclude that the genomic architectures of genetic and physical interactions are independent, with important implications for gene regulatory evolution, interpretation of genetic association studies, and precision medicine.

The MHC in the era of next-generation sequencing: Implications for bridging structure with function

The MHC continues to have the most disease-associations compared to other regions of the human genome, even in the genome-wide association study (GWAS) and single nucleotide polymorphism (SNP) era. Analysis of non-coding variation and their impact on the level of expression of HLA allotypes has shed new light on the potential mechanisms underlying HLA disease associations and alloreactivity in transplantation. Next-generation sequencing (NGS) technology has the capability of delineating the phase of variants in the HLA antigen-recognition site (ARS) with non-coding regulatory polymorphisms. These relationships are critical for understanding the qualitative and quantitative implications of HLA gene diversity. This article summarizes current understanding of non-coding region variation of HLA loci, the consequences of regulatory variation on HLA expression, the role for evolution in shaping lineage-specific expression, and the impact of HLA expression on disease susceptibility and transplantation outcomes. A role for phased sequencing methods for the MHC, and perspectives for future directions in basic and applied immunogenetic studies of the MHC are presented.

Type 1 Diabetes Mellitus-Associated Genetic Variants Contribute to Overlapping Immune Regulatory Networks

Type 1 diabetes (T1D) is a chronic metabolic disorder characterized by the autoimmune destruction of insulin-producing pancreatic islet beta cells in genetically predisposed individuals. Genome-wide association studies (GWAS) have identified over 60 risk regions across the human genome, marked by single nucleotide polymorphisms (SNPs), which confer genetic predisposition to T1D. There is increasing evidence that disease-associated SNPs can alter gene expression through spatial interactions that involve distal loci, in a tissue- and development-specific manner. Here, we used three-dimensional (3D) genome organization data to identify genes that physically co-localized with DNA regions that contained T1D-associated SNPs in the nucleus. Analysis of these SNP-gene pairs using the Genotype-Tissue Expression database identified a subset of SNPs that significantly affected gene expression. We identified 246 spatially regulated genes including HLA-DRB1, LAT, MICA, BTN3A2, CTLA4, CD226, NOTCH1, TRIM26, PTEN, TYK2, CTSH, and FLRT3, which exhibit tissue-specific effects in multiple tissues. We observed that the T1D-associated variants interconnect through networks that form part of the immune regulatory pathways, including immune-cell activation, cytokine signaling, and programmed cell death protein-1 (PD-1). Our results implicate T1D-associated variants in tissue and cell-type specific regulatory networks that contribute to pancreatic beta cell inflammation and destruction, adaptive immune signaling, and immune-cell proliferation and activation. A number of other regulatory changes we identified are not typically considered to be central to the pathology of T1D. Collectively, our data represent a novel resource for the hypothesis-driven development of diagnostic, prognostic, and therapeutic interventions in T1D.

Molecular evolution of elements controlling HLA-C expression: Adaptation to a role as a killer-cell immunoglobulin-like receptor ligand regulating natural killer cell function

The regulatory elements controlling the transcription of the HLA-A, HLA-B, and HLA-C genes have been extensively studied and compared. However, few studies have considered regulatory differences in the HLA genes from the perspective of their role as ligands for the killer-cell immunoglobulin-like receptor (KIR) family of HLA receptors expressed by natural killer (NK) cells. HLA-C is the most recently evolved gene, and there is considerable evidence pointing to its emergence as a specialized KIR ligand playing a major role in the missing-self recognition system of NK cells. Here I evaluate gene-specific differences in regulatory elements of the HLA genes, showing alterations that are consistent with the adaptation of HLA-C to a role in NK cell regulation.

Cell-type-specific eQTL of primary melanocytes facilitates identification of melanoma susceptibility genes

Most expression quantitative trait locus (eQTL) studies to date have been performed in heterogeneous tissues as opposed to specific cell types. To better understand the cell-type-specific regulatory landscape of human melanocytes, which give rise to melanoma but account for <5% of typical human skin biopsies, we performed an eQTL analysis in primary melanocyte cultures from 106 newborn males. We identified 597,335 cis-eQTL SNPs prior to linkage disequilibrium (LD) pruning and 4997 eGenes (FDR < 0.05). Melanocyte eQTLs differed considerably from those identified in the 44 GTEx tissue types, including skin. Over a third of melanocyte eGenes, including key genes in melanin synthesis pathways, were unique to melanocytes compared to those of GTEx skin tissues or TCGA melanomas. The melanocyte data set also identified trans-eQTLs, including those connecting a pigmentation-associated functional SNP with four genes, likely through cis-regulation of IRF4 Melanocyte eQTLs are enriched in cis-regulatory signatures found in melanocytes as well as in melanoma-associated variants identified through genome-wide association studies. Melanocyte eQTLs also colocalized with melanoma GWAS variants in five known loci. Finally, a transcriptome-wide association study using melanocyte eQTLs uncovered four novel susceptibility loci, where imputed expression levels of five genes (ZFP90, HEBP1, MSC, CBWD1, and RP11-383H13.1) were associated with melanoma at genome-wide significant P-values. Our data highlight the utility of lineage-specific eQTL resources for annotating GWAS findings, and present a robust database for genomic research of melanoma risk and melanocyte biology.

Renal compartment-specific genetic variation analyses identify new pathways in chronic kidney disease

Chronic kidney disease (CKD), a condition in which the kidneys are unable to clear waste products, affects 700 million people globally. Genome-wide association studies (GWASs) have identified sequence variants for CKD; however, the biological basis of these GWAS results remains poorly understood. To address this issue, we created an expression quantitative trait loci (eQTL) atlas for the glomerular and tubular compartments of the human kidney. Through integrating the CKD GWAS with eQTL, single-cell RNA sequencing and regulatory region maps, we identified novel genes for CKD. Putative causal genes were enriched for proximal tubule expression and endolysosomal function, where DAB2, an adaptor protein in the TGF-β pathway, formed a central node. Functional experiments confirmed that reducing Dab2 expression in renal tubules protected mice from CKD. In conclusion, compartment-specific eQTL analysis is an important avenue for the identification of novel genes and cellular pathways involved in CKD development and thus potential new opportunities for its treatment.

Discovering in vivo cytokine-eQTL interactions from a lupus clinical trial

BACKGROUND

Cytokines are critical to human disease and are attractive therapeutic targets given their widespread influence on gene regulation and transcription. Defining the downstream regulatory mechanisms influenced by cytokines is central to defining drug and disease mechanisms. One promising strategy is to use interactions between expression quantitative trait loci (eQTLs) and cytokine levels to define target genes and mechanisms.

RESULTS

In a clinical trial for anti-IL-6 in patients with systemic lupus erythematosus, we measure interferon (IFN) status, anti-IL-6 drug exposure, and whole blood genome-wide gene expression at three time points. We show that repeat transcriptomic measurements increases the number of cis eQTLs identified compared to using a single time point. We observe a statistically significant enrichment of in vivo eQTL interactions with IFN status and anti-IL-6 drug exposure and find many novel interactions that have not been previously described. Finally, we find transcription factor binding motifs interrupted by eQTL interaction SNPs, which point to key regulatory mediators of these environmental stimuli and therefore potential therapeutic targets for autoimmune diseases. In particular, genes with IFN interactions are enriched for ISRE binding site motifs, while those with anti-IL-6 interactions are enriched for IRF4 motifs.

CONCLUSIONS

This study highlights the potential to exploit clinical trial data to discover in vivo eQTL interactions with therapeutically relevant environmental variables.

Systematic approach demonstrates enrichment of multiple interactions between non-HLA risk variants and HLA-DRB1 risk alleles in rheumatoid arthritis

OBJECTIVE

In anti-citrullinated protein antibody positive rheumatoid arthritis (ACPA-positive RA), a particular subset of HLA-DRB1 alleles, called shared epitope (SE) alleles, is a highly influential genetic risk factor. Here, we investigated whether non-HLA single nucleotide polymorphisms (SNP), conferring low disease risk on their own, interact with SE alleles more frequently than expected by chance and if such genetic interactions influence the HLA-DRB1 SE effect concerning risk to ACPA-positive RA.

METHODS

We computed the attributable proportion (AP) due to additive interaction at genome-wide level for two independent ACPA-positive RA cohorts: the Swedish epidemiological investigation of rheumatoid arthritis (EIRA) and the North American rheumatoid arthritis consortium (NARAC). Then, we tested for differences in the AP p value distributions observed for two groups of SNPs, non-associated and associated with disease. We also evaluated whether the SNPs in interaction with HLA-DRB1 were cis-eQTLs in the SE alleles context in peripheral blood mononuclear cells from patients with ACPA-positive RA (SE-eQTLs).

RESULTS

We found a strong enrichment of significant interactions (AP p<0.05) between the HLA-DRB1 SE alleles and the group of SNPs associated with ACPA-positive RA in both cohorts (Kolmogorov-Smirnov test D=0.35 for EIRA and D=0.25 for NARAC, p<2.2e-16 for both). Interestingly, 564 out of 1492 SNPs in consistent interaction for both cohorts were significant SE-eQTLs. Finally, we observed that the effect size of HLA-DRB1 SE alleles for disease decreases from 5.2 to 2.5 after removal of the risk alleles of the two top interacting SNPs (rs2476601 and rs10739581).

CONCLUSION

Our data demonstrate that there are massive genetic interactions between the HLA-DRB1 SE alleles and non-HLA genetic variants in ACPA-positive RA.

Identification of a Genomic Region between SLC29A1 and HSP90AB1 Associated with Risk of Bevacizumab-Induced Hypertension: CALGB 80405 (Alliance)

Purpose: Bevacizumab is a VEGF-specific angiogenesis inhibitor indicated as an adjunct to chemotherapy for the treatment of multiple cancers. Hypertension is commonly observed during bevacizumab treatment, and high-grade toxicity can limit therapy or lead to cardiovascular complications. The factors that contribute to interindividual variability in blood pressure rise during bevacizumab treatment are not well understood.Experimental Design: To identify genomic regions associated with bevacizumab-induced hypertension risk, sequencing of candidate genes and flanking regulatory regions was performed on 61 patients treated with bevacizumab (19 cases developed early-onset grade 3 hypertension and 42 controls had no reported hypertension in the first six cycles of treatment). SNP-based tests for common variant associations and gene-based tests for rare variant associations were performed in 174 candidate genes.Results: Four common variants in independent linkage disequilibrium blocks between SLC29A1 and HSP90AB1 were among the top associations. Validation in larger bevacizumab-treated cohorts supported association between rs9381299 with early grade 3+ hypertension (P = 0.01; OR, 2.4) and systolic blood pressure >180 mm Hg (P = 0.02; OR, 2.1). rs834576 was associated with early grade 3+ hypertension in CALGB 40502 (P = 0.03; OR, 2.9). These SNP regions are enriched for regulatory elements that may potentially increase gene expression. In vitro overexpression of SLC29A1 in human endothelial cells disrupted adenosine signaling and reduced nitric oxide levels that were further lowered upon bevacizumab exposure.Conclusions: The genomic region between SLC29A1 and HSP90AB1 and its role in regulating adenosine signaling are key targets for further investigation into the pathogenesis of bevacizumab-induced hypertension. Clin Cancer Res; 24(19); 4734-44. ©2018 AACR.

Translating GWAS in rheumatic disease: approaches to establishing mechanism and function for genetic associations with ankylosing spondylitis

Ankylosing spondylitis (AS) is a highly heritable chronic inflammatory arthritis characterized by osteoproliferation, fusion of affected joints and systemic manifestations. Many disease associations for AS have been reported through genome-wide association studies; however, identifying modulated genes and functional mechanism remains challenging. This review summarizes current genetic associations involving AS and describes strategic approaches for functional follow-up of disease-associated variants. Fine mapping using methods leveraging Bayesian approaches are outlined. Evidence highlighting the importance of context specificity for regulatory variants is reviewed, noting current evidence in AS for the relevant cell and tissue type to conduct such analyses. Technological advances for understanding the regulatory landscape within which functional variants may act are discussed using exemplars. Approaches include defining regulatory elements based on chromatin accessibility, effects of variants on genes at a distance through evidence of physical interactions (chromatin conformation capture), expression quantitative trait loci mapping and single-cell methodologies. Opportunities for mechanistic studies to investigate the function of specific variants, regulatory elements and genes enabled by genome editing using clustered regularly interspaced short palindromic repeats/Cas9 are also described. Further progress in our understanding of the genetics of AS through functional genomic and epigenomic approaches offers new opportunities to understand mechanism and develop innovative treatments.

Fasting and time of day independently modulate circadian rhythm relevant gene expression in adipose and skin tissue

BACKGROUND

Intermittent fasting and time-restricted diets are associated with lower risk biomarkers for cardio-metabolic disease. The shared mechanisms underpinning the similar physiological response to these events is not established, but circadian rhythm could be involved. Here we investigated the transcriptional response to fasting in a large cross-sectional study of adipose and skin tissue from healthy volunteers (N = 625) controlling for confounders of circadian rhythm: time of day and season.

RESULTS

We identified 367 genes in adipose and 79 in skin whose expression levels were associated (FDR < 5%) with hours of fasting conditionally independent of time of day and season, with 19 genes common to both tissues. Among these genes, we replicated 38 in human, 157 in non-human studies, and 178 are novel associations. Fasting-responsive genes were enriched for regulation of and response to circadian rhythm. We identified 99 genes in adipose and 54 genes in skin whose expression was associated to time of day; these genes were also enriched for circadian rhythm processes. In genes associated to both exposures the effect of time of day was stronger and in an opposite direction to that of hours fasted. We also investigated the relationship between fasting and genetic regulation of gene expression, including GxE eQTL analysis to identify personal responses to fasting.

CONCLUSION

This study robustly implicates circadian rhythm genes in the response to hours fasting independently of time of day, seasonality, age and BMI. We identified tissue-shared and tissue-specific differences in the transcriptional response to fasting in a large sample of healthy volunteers.

Reduced monocyte and macrophage TNFSF15/TL1A expression is associated with susceptibility to inflammatory bowel disease

Chronic inflammation in inflammatory bowel disease (IBD) results from a breakdown of intestinal immune homeostasis and compromise of the intestinal barrier. Genome-wide association studies have identified over 200 genetic loci associated with risk for IBD, but the functional mechanisms of most of these genetic variants remain unknown. Polymorphisms at the TNFSF15 locus, which encodes the TNF superfamily cytokine commonly known as TL1A, are associated with susceptibility to IBD in multiple ethnic groups. In a wide variety of murine models of inflammation including models of IBD, TNFSF15 promotes immunopathology by signaling through its receptor DR3. Such evidence has led to the hypothesis that expression of this lymphocyte costimulatory cytokine increases risk for IBD. In contrast, here we show that the IBD-risk haplotype at TNFSF15 is associated with decreased expression of the gene by peripheral blood monocytes in both healthy volunteers and IBD patients. This association persists under various stimulation conditions at both the RNA and protein levels and is maintained after macrophage differentiation. Utilizing a "recall-by-genotype" bioresource for allele-specific expression measurements in a functional fine-mapping assay, we localize the polymorphism controlling TNFSF15 expression to the regulatory region upstream of the gene. Through a T cell costimulation assay, we demonstrate that genetically regulated TNFSF15 has functional relevance. These findings indicate that genetically enhanced expression of TNFSF15 in specific cell types may confer protection against the development of IBD.

An eQTL Landscape of Kidney Tissue in Human Nephrotic Syndrome

Expression quantitative trait loci (eQTL) studies illuminate the genetics of gene expression and, in disease research, can be particularly illuminating when using the tissues directly impacted by the condition. In nephrology, there is a paucity of eQTL studies of human kidney. Here, we used whole-genome sequencing (WGS) and microdissected glomerular (GLOM) and tubulointerstitial (TI) transcriptomes from 187 individuals with nephrotic syndrome (NS) to describe the eQTL landscape in these functionally distinct kidney structures. Using MatrixEQTL, we performed cis-eQTL analysis on GLOM (n = 136) and TI (n = 166). We used the Bayesian "Deterministic Approximation of Posteriors" (DAP) to fine-map these signals, eQTLBMA to discover GLOM- or TI-specific eQTLs, and single-cell RNA-seq data of control kidney tissue to identify the cell type specificity of significant eQTLs. We integrated eQTL data with an IgA Nephropathy (IgAN) GWAS to perform a transcriptome-wide association study (TWAS). We discovered 894 GLOM eQTLs and 1,767 TI eQTLs at FDR < 0.05. 14% and 19% of GLOM and TI eQTLs, respectively, had >1 independent signal associated with its expression. 12% and 26% of eQTLs were GLOM specific and TI specific, respectively. GLOM eQTLs were most significantly enriched in podocyte transcripts and TI eQTLs in proximal tubules. The IgAN TWAS identified significant GLOM and TI genes, primarily at the HLA region. In this study, we discovered GLOM and TI eQTLs, identified those that were tissue specific, deconvoluted them into cell-specific signals, and used them to characterize known GWAS alleles. These data are available for browsing and download via our eQTL browser, "nephQTL."

Deep learning sequence-based ab initio prediction of variant effects on expression and disease risk

Key challenges for human genetics, precision medicine and evolutionary biology include deciphering the regulatory code of gene expression and understanding the transcriptional effects of genome variation. However, this is extremely difficult because of the enormous scale of the noncoding mutation space. We developed a deep learning-based framework, ExPecto, that can accurately predict, ab initio from a DNA sequence, the tissue-specific transcriptional effects of mutations, including those that are rare or that have not been observed. We prioritized causal variants within disease- or trait-associated loci from all publicly available genome-wide association studies and experimentally validated predictions for four immune-related diseases. By exploiting the scalability of ExPecto, we characterized the regulatory mutation space for human RNA polymerase II-transcribed genes by in silico saturation mutagenesis and profiled > 140 million promoter-proximal mutations. This enables probing of evolutionary constraints on gene expression and ab initio prediction of mutation disease effects, making ExPecto an end-to-end computational framework for the in silico prediction of expression and disease risk.

Enhancer histone-QTLs are enriched on autoimmune risk haplotypes and influence gene expression within chromatin networks

Genetic variants can confer risk to complex genetic diseases by modulating gene expression through changes to the epigenome. To assess the degree to which genetic variants influence epigenome activity, we integrate epigenetic and genotypic data from lupus patient lymphoblastoid cell lines to identify variants that induce allelic imbalance in the magnitude of histone post-translational modifications, referred to herein as histone quantitative trait loci (hQTLs). We demonstrate that enhancer hQTLs are enriched on autoimmune disease risk haplotypes and disproportionately influence gene expression variability compared with non-hQTL variants in strong linkage disequilibrium. We show that the epigenome regulates HLA class II genes differently in individuals who carry HLA-DR3 or HLA-DR15 haplotypes, resulting in differential 3D chromatin conformation and gene expression. Finally, we identify significant expression QTL (eQTL) x hQTL interactions that reveal substructure within eQTL gene expression, suggesting potential implications for functional genomic studies that leverage eQTL data for subject selection and stratification.

Disease risk variants can exert their influence on phenotypes by altering epigenome function. Here, Pelikan et al. show that variants inducing allelic imbalance in histone marks in lymphoblastoid cell lines from lupus patients are enriched in autoimmune disease haplotypes and influence gene expression.

Genetics of trans-regulatory variation in gene expression

Heritable variation in gene expression forms a crucial bridge between genomic variation and the biology of many traits. However, most expression quantitative trait loci (eQTLs) remain unidentified. We mapped eQTLs by transcriptome sequencing in 1012 yeast segregants. The resulting eQTLs accounted for over 70% of the heritability of mRNA levels, allowing comprehensive dissection of regulatory variation. Most genes had multiple eQTLs. Most expression variation arose from trans-acting eQTLs distant from their target genes. Nearly all trans-eQTLs clustered at 102 hotspot locations, some of which influenced the expression of thousands of genes. Fine-mapped hotspot regions were enriched for transcription factor genes. While most genes had a local eQTL, most of these had no detectable effects on the expression of other genes in trans. Hundreds of non-additive genetic interactions accounted for small fractions of expression variation. These results reveal the complexity of genetic influences on transcriptome variation in unprecedented depth and detail.

Genome-wide association and HLA fine-mapping studies identify risk loci and genetic pathways underlying allergic rhinitis

Allergic rhinitis is the most common clinical presentation of allergy, affecting 400 million people worldwide, with increasing incidence in westernized countries^1,2. To elucidate the genetic architecture and understand the underlying disease mechanisms, we carried out a meta-analysis of allergic rhinitis in 59,762 cases and 152,358 controls of European ancestry and identified a total of 41 risk loci for allergic rhinitis, including 20 loci not previously associated with allergic rhinitis, which were confirmed in a replication phase of 60,720 cases and 618,527 controls. Functional annotation implicated genes involved in various immune pathways, and fine mapping of the HLA region suggested amino acid variants important for antigen binding. We further performed genome-wide association study (GWAS) analyses of allergic sensitization against inhalant allergens and nonallergic rhinitis, which suggested shared genetic mechanisms across rhinitis-related traits. Future studies of the identified loci and genes might identify novel targets for treatment and prevention of allergic rhinitis.

Identification of ST3AGL4, MFHAS1, CSNK2A2 and CD226 as loci associated with systemic lupus erythematosus (SLE) and evaluation of SLE genetics in drug repositioning

OBJECTIVES

Systemic lupus erythematosus (SLE) is a prototype autoimmune disease with a strong genetic component in its pathogenesis. Through genome-wide association studies (GWAS), we recently identified 10 novel loci associated with SLE and uncovered a number of suggestive loci requiring further validation. This study aimed to validate those loci in independent cohorts and evaluate the role of SLE genetics in drug repositioning.

METHODS

We conducted GWAS and replication studies involving 12 280 SLE cases and 18 828 controls, and performed fine-mapping analyses to identify likely causal variants within the newly identified loci. We further scanned drug target databases to evaluate the role of SLE genetics in drug repositioning.

RESULTS

We identified three novel loci that surpassed genome-wide significance, including ST3AGL4 (rs13238909, pmeta=4.40E-08), MFHAS1 (rs2428, pmeta=1.17E-08) and CSNK2A2 (rs2731783, pmeta=1.08E-09). We also confirmed the association of CD226 locus with SLE (rs763361, pmeta=2.45E-08). Fine-mapping and functional analyses indicated that the putative causal variants in CSNK2A2 locus reside in an enhancer and are associated with expression of CSNK2A2 in B-lymphocytes, suggesting a potential mechanism of association. In addition, we demonstrated that SLE risk genes were more likely to be interacting proteins with targets of approved SLE drugs (OR=2.41, p=1.50E-03) which supports the role of genetic studies to repurpose drugs approved for other diseases for the treatment of SLE.

CONCLUSION

This study identified three novel loci associated with SLE and demonstrated the role of SLE GWAS findings in drug repositioning.

Genetic-Driven Druggable Target Identification and Validation

Choosing the right biological target is the critical primary decision for the development of new drugs. Systematic genetic association testing of both human diseases and quantitative traits, along with resultant findings of coincident associations between them, is becoming a powerful approach to infer drug targetable candidates and generate in vitro tests to identify compounds that can modulate them therapeutically. Here, we discuss opportunities and challenges, and infer criteria for the optimal use of genetic findings in the drug discovery pipeline.

Disease-specific regulation of gene expression in a comparative analysis of juvenile idiopathic arthritis and inflammatory bowel disease

BACKGROUND

The genetic and immunological factors that contribute to differences in susceptibility and progression between sub-types of inflammatory and autoimmune diseases continue to be elucidated. Inflammatory bowel disease and juvenile idiopathic arthritis are both clinically heterogeneous and known to be due in part to abnormal regulation of gene activity in diverse immune cell types. Comparative genomic analysis of these conditions is expected to reveal differences in underlying genetic mechanisms of disease.

METHODS

We performed RNA-Seq on whole blood samples from 202 patients with oligoarticular, polyarticular, or systemic juvenile idiopathic arthritis, or with Crohn's disease or ulcerative colitis, as well as healthy controls, to characterize differences in gene expression. Gene ontology analysis combined with Blood Transcript Module and Blood Informative Transcript analysis was used to infer immunological differences. Comparative expression quantitative trait locus (eQTL) analysis was used to quantify disease-specific regulation of transcript abundance.

RESULTS

A pattern of differentially expressed genes and pathways reveals a gradient of disease spanning from healthy controls to oligoarticular, polyarticular, and systemic juvenile idiopathic arthritis (JIA); Crohn's disease; and ulcerative colitis. Transcriptional risk scores also provide good discrimination of controls, JIA, and IBD. Most eQTL are found to have similar effects across disease sub-types, but we also identify disease-specific eQTL at loci associated with disease by GWAS.

CONCLUSION

JIA and IBD are characterized by divergent peripheral blood transcriptomes, the genetic regulation of which displays limited disease specificity, implying that disease-specific genetic influences are largely independent of, or downstream of, eQTL effects.

Identifying gene targets for brain-related traits using transcriptomic and methylomic data from blood

Understanding the difference in genetic regulation of gene expression between brain and blood is important for discovering genes for brain-related traits and disorders. Here, we estimate the correlation of genetic effects at the top-associated cis-expression or -DNA methylation (DNAm) quantitative trait loci (cis-eQTLs or cis-mQTLs) between brain and blood (r _b ). Using publicly available data, we find that genetic effects at the top cis-eQTLs or mQTLs are highly correlated between independent brain and blood samples ([Formula: see text] for cis-eQTLs and [Formula: see text] for cis-mQTLs). Using meta-analyzed brain cis-eQTL/mQTL data (n = 526 to 1194), we identify 61 genes and 167 DNAm sites associated with four brain-related phenotypes, most of which are a subset of the discoveries (97 genes and 295 DNAm sites) using data from blood with larger sample sizes (n = 1980 to 14,115). Our results demonstrate the gain of power in gene discovery for brain-related phenotypes using blood cis-eQTL/mQTL data with large sample sizes.

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.

Diminished CXCR5 expression in peripheral blood of patients with Sjögren's syndrome may relate to both genotype and salivary gland homing

Genetic investigations of Sjögren's syndrome (SS) have identified a susceptibility locus at p23.3 of chromosome 11, which contains the CXCR5 gene. C-X-C motif chemokine receptor 5 (CXCR5) is a chemokine receptor expressed on B and T cell subsets, and binds the chemotactic ligand C-X-C motif chemokine ligand 13 (CXCL13). In this study we aimed to link the genetic association with functional effects and explore the CXCR5/CXCL13 axis in SS. Expression quantitative trait loci analysis of the 11q23.3 locus was performed using B cell mRNA expression data from genotyped individuals. Lymphocyte surface markers were assessed by flow cytometry, and CXCL13 levels by a proximity extension assay. CXCR5+ and CXCL13+ cells in minor salivary glands were detected using immunohistochemistry. Our results demonstrated that SS-associated genetic polymorphisms affected the expression of CXCR5 (P < 0·01). Notably, a decreased percentage of CXCR5+ cells, with lower CXCR5 expression, was observed for most circulating B and T cell subsets in SS patients, reaching statistical significance in CD19+ CD27+ immunoglobulin (Ig)D+ marginal zone (P < 0·001), CD19+ CD27+ IgD- memory (P < 0·05) and CD27-IgD double-negative (P < 0·01) B cells and CD4+ CXCR3- CCR6+ Th17 cells (P < 0·05). CXCL13 levels were increased in patient plasma (P < 0·001), and immunohistochemical staining revealed expression of CXCL13 and higher numbers of CXCR5+ cells (P < 0·0001) within focal infiltrates and interstitially in salivary glands of SS patients. In conclusion, we link a genetic susceptibility allele for SS to a functional phenotype in terms of decreased CXCR5 expression. The decrease of CXCR5+ cells in circulation was also related to homing of B and T cells to the autoimmune target organ. Therapeutic drugs targeting the CXCR5/CXCL13 axis may be useful in SS.