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Expression quantitative trait loci (eQTLs) studies provide associations of genetic variants with gene expression but fall short of pinpointing functionally important eQTLs. Here, using H3K27ac HiChIP assays, we mapped eQTLs overlapping active cis -regulatory elements that interact with their target gene promoters (promoter-interacting eQTLs, pieQTLs) in five common immune cell types (Database of Immune Cell Expression, Expression quantitative trait loci and Epigenomics (DICE) cis -interactome project). This approach allowed us to identify functionally important eQTLs and show mechanisms that explain their cell-type restriction. We also devised an approach to eQTL discovery that relies on HiChIP-based promoter interaction maps as a structural framework for deciding which SNPs to test for association with gene expression, and observe ultra-long-distance pieQTLs (>1 megabase away), including several disease-risk variants. We validated the functional role of pieQTLs using reporter assays, CRISPRi, dCas9-tiling guides and Cas9-mediated base-pair editing. In this article we present a method for functional eQTL discovery and provide insights into relevance of noncoding variants for cell-specific gene regulation and for disease association beyond conventional eQTL mapping. H3K27ac HiChIP analysis helps to identify promoter-interacting expression quantitative trait loci (pieQTLs) in five common immune cell types. Some pieQTLs overlap with nontranscribed promoters that act as enhancers.

Common genetic polymorphisms associated with COVID-19 illness can be utilized for discovering molecular pathways and cell types driving disease pathogenesis. Given the importance of immune cells in the pathogenesis of COVID-19 illness, here we assessed the effects of COVID-19-risk variants on gene expression in a wide range of immune cell types. Transcriptome-wide association study and colocalization analysis revealed putative causal genes and the specific immune cell types where gene expression is most influenced by COVID-19-risk variants. Notable examples include OAS1 in non-classical monocytes, DTX1 in B cells, IL10RB in NK cells, CXCR6 in follicular helper T cells, CCR9 in regulatory T cells and ARL17A in T H 2 cells. By analysis of transposase accessible chromatin and H3K27ac-based chromatin-interaction maps of immune cell types, we prioritized potentially functional COVID-19-risk variants. Our study highlights the potential of COVID-19 genetic risk variants to impact the function of diverse immune cell types and influence severe disease manifestations. Immune cells are important in the pathogenesis of COVID-19. Here the authors assessed the effects of COVID-19-risk variants on gene expression in a range of immune cell types, highlighting their potential to impact the function of diverse immune cell types and influence severe disease.

Genetic variants at the PTPN2 locus, which encodes the tyrosine phosphatase PTPN2, cause reduced gene expression and are linked to rheumatoid arthritis (RA) and other autoimmune diseases. PTPN2 inhibits signaling through the T cell and cytokine receptors, and loss of PTPN2 promotes T cell expansion and CD4- and CD8-driven autoimmunity. However, it remains unknown whether loss of PTPN2 in FoxP3+ regulatory T cells (Tregs) plays a role in autoimmunity. Here we aimed to model human autoimmune-predisposing PTPN2 variants, the presence of which results in a partial loss of PTPN2 expression, in mouse models of RA. We identified that reduced expression of Ptpn2 enhanced the severity of autoimmune arthritis in the T cell-dependent SKG mouse model and demonstrated that this phenotype was mediated through a Treg-intrinsic mechanism. Mechanistically, we found that through dephosphorylation of STAT3, PTPN2 inhibits IL-6-driven pathogenic loss of FoxP3 after Tregs have acquired RORγt expression, at a stage when chromatin accessibility for STAT3-targeted IL-17-associated transcription factors is maximized. We conclude that PTPN2 promotes FoxP3 stability in mouse RORγt+ Tregs and that loss of function of PTPN2 in Tregs contributes to the association between PTPN2 and autoimmunity.

With the continued promise of immunotherapy for treating cancer, understanding how host genetics contributes to the tumor immune microenvironment (TIME) is essential to tailoring cancer screening and treatment strategies. Here, we study 1084 eQTLs affecting the TIME found through analysis of The Cancer Genome Atlas and literature curation. These TIME eQTLs are enriched in areas of active transcription, and associate with gene expression in specific immune cell subsets, such as macrophages and dendritic cells. Polygenic score models built with TIME eQTLs reproducibly stratify cancer risk, survival and immune checkpoint blockade (ICB) response across independent cohorts. To assess whether an eQTL-informed approach could reveal potential cancer immunotherapy targets, we inhibit CTSS , a gene implicated by cancer risk and ICB response-associated polygenic models; CTSS inhibition results in slowed tumor growth and extended survival in vivo. These results validate the potential of integrating germline variation and TIME characteristics for uncovering potential targets for immunotherapy. The contribution of genetic factors to the tumour immune microenvironment (TIME) remains to be investigated. Here, the authors suggest the role of TIME eQTLs for target genes involved in reversing immune suppressive features.

Brain tumors in children are a devastating disease in a high proportion of patients. Owing to inconsistent results in clinical trials in unstratified patients, the role of immunotherapy remains unclear. We performed an in-depth survey of the single-cell transcriptomes and clonal relationship of intra-tumoral T cells from children with brain tumors. Our results demonstrate that a large fraction of T cells in the tumor tissue are clonally expanded with the potential to recognize tumor antigens. Such clonally expanded T cells display enrichment of transcripts linked to effector function, tissue residency, immune checkpoints and signatures of neoantigen-specific T cells and immunotherapy response. We identify neoantigens in pediatric brain tumors and show that neoantigen-specific T cell gene signatures are linked to better survival outcomes. Notably, among the patients in our cohort, we observe substantial heterogeneity in the degree of clonal expansion and magnitude of T cell response. Our findings suggest that characterization of intra-tumoral T cell responses may enable selection of patients for immunotherapy, an approach that requires prospective validation in clinical trials.

Cancer/testis antigens (CTA) are a heterogeneous group of antigens that are expressed preferentially in tumor cells and testis. Based on this definition the human membrane-associated phospholipase A1 beta (lipase family member I, LIPI) has been identified as CTA. The high homology of LIPI and the membrane-associated phospholipase A1 alpha (lipase family member H, LIPH) suggests that both genes are derived from a common ancestor by gene duplication. In contrast to human LIPI, human LIPH is expressed in several tissues. LIPI sequences have only been identified in mammals. Here, we describe the identification of LIPI in non-mammalian vertebrates. Based on the conserved genomic organization of LIPI and LIPH we identified sequences for both lipases in birds and fishes. In all vertebrates the LIPI locus is neighbored by a member of the RNA binding motif (RBM) family, RBM11. By sequencing of reverse transcriptase-polymerase chain reaction products we determined the sequences of LIPI and LIPH messenger RNA from broilers. We found that the sequence homology between LIPI and LIPH is much higher in non-mammalian species than in mammals. In addition, we found broad expression of LIPI in broilers, resembling the expression profile of LIPH. Our data suggest that LIPI is a CTA only in mammalian species and that the unique sequence features of the mammalian LIPI/RBM11 locus have evolved together with the CTA-like expression pattern of LIPI.

ABSTRACT Common genetic polymorphisms associated with severity of COVID-19 illness can be utilized for discovering molecular pathways and cell types driving disease pathogenesis. Here, we assessed the effects of 679 COVID-19-risk variants on gene expression in a wide-range of immune cell types. Severe COVID-19-risk variants were significantly associated with the expression of 11 protein-coding genes, and overlapped with either target gene promoter or cis-regulatory regions that interact with target promoters in the cell types where their effects are most prominent. For example, we identified that the association between variants in the 3p21.31 risk locus and the expression of CCR2 in classical monocytes is likely mediated through an active cis-regulatory region that interacted with CCR2 promoter specifically in monocytes. The expression of several other genes showed prominent genotype-dependent effects in non-classical monocytes, NK cells, B cells, or specific T cell subtypes, highlighting the potential of COVID-19 genetic risk variants to impact the function of diverse immune cell types and influence severe disease manifestations. Competing Interest Statement The authors have declared no competing interest. Footnotes * ↵6 Joint senior authors.

The systemic lupus erythematosus (SLE) is an incurable autoimmune disease disproportionately affecting women and may lead to damage in multiple different organs. The marked heterogeneity in its clinical manifestations is a major obstacle in finding targeted treatments and involvement of multiple immune cell types further increases this complexity. Thus, identifying molecular subtypes that best correlate with disease heterogeneity and severity as well as deducing molecular cross-talk among major immune cell types that lead to disease progression are critical steps in the development of more informed therapies for SLE. Here we profile and analyze gene expression of six major circulating immune cell types from patients with well-characterized SLE (classical monocytes (n=64), T cells (n=24), neutrophils (n=24), B cells (n=20), conventional (n=20) and plasmacytoid (n=22) dendritic cells) and from healthy control subjects. Our results show that the interferon (IFN) response signature was the major molecular feature that classified SLE patients into two distinct groups: IFN-signature negative (IFNneg) and positive (IFNpos). We show that the gene expression signature of IFN response was consistent (i) across all immune cell types, (ii) all single cells profiled from three IFNpos donors using single-cell RNA-seq, and (iii) longitudinal samples of the same patient. For a better understanding of molecular differences of IFNpos versus IFNneg patients, we combined differential gene expression analysis with differential Weighted Gene Co-expression Network Analysis (WGCNA), which revealed a relatively small list of genes from classical monocytes including two known immune modulators, one the target of an approved therapeutic for SLE (TNFSF13B/BAFF: belimumab) and one itself a therapeutic for Rheumatoid Arthritis (IL1RN: anakinra). For a more integrative understanding of the cross-talk among different cell types and to identify potentially novel gene or pathway connections, we also developed a novel gene co-expression analysis method for joint analysis of multiple cell types named integrated WGNCA (iWGCNA). This method revealed an interesting cross-talk between T and B cells highlighted by a significant enrichment in the expression of known markers of T follicular helper cells (Tfh), which also correlate with disease severity in the context of IFNpos patients. Interestingly, higher expression of BAFF from all myeloid cells also shows a strong correlation with enrichment in the expression of genes in T cells that may mark circulating Tfh cells or related memory cell populations. These cell types have been shown to promote B cell class-switching and antibody production, which are well-characterized in SLE patients. In summary, we generated a large-scale gene expression dataset from sorted immune cell populations and present a novel computational approach to analyze such data in an integrative fashion in the context of an autoimmune disease. Our results reveal the power of a hypothesis-free and data-driven approach to discover drug targets and reveal novel cross-talk among multiple immune cell types specific to a subset of SLE patients. This approach is immediately useful for studying autoimmune diseases and is applicable in other contexts where gene expression profiling is possible from multiple cell types within the same tissue compartment.

With the continued promise of immunotherapy as an avenue for treating cancer, understanding how host genetics contributes to the tumor immune microenvironment (TIME) is essential to tailoring cancer screening and treatment strategies. Approaches that intersect SNP modifiers of molecular phenotype, such as gene expression, with disease phenotypes have shown promise for implicating causal genetic factors. Here we evaluated 194 literature-curated TIME associations and 890 associations detected with 157 immune phenotype (IP) components found using genotypes from over 8,000 individuals in The Cancer Genome Atlas. Of these 1084, 233 associations comprising 219 unique TIME-SNPs were also cancer relevant, associating with cancer risk, survival, and/or immunotherapy treatment response. Many cancer relevant TIME-SNPS overlapped regions of active transcription, and were associated with gene expression in specific immune cell subsets, such as macrophages and dendritic cells. TIME-SNPs associated with cancer risk and response to immunotherapy implicated genes involved in antigen presentation, especially by antigen presenting cells. The strongest associations with survival were with PD-L1 and CTLA-4, suggesting that SNPs modifying the potential for immune evasion could contribute to disease progression. To assess whether our approach could reveal novel cancer immunotherapy targets, we inhibited CTSS, a gene implicated by cancer risk and immunotherapy response-associated TIME-SNPs; CTSS inhibition resulted in slowed tumor growth and extended survival in vivo. These results validate the potential of cancer relevant TIME-SNPs to implicate target genes for countering immune suppressive characteristics of the TIME and set the stage for future host genetics analysis integrating germline variation and TIME characteristics. Competing Interest Statement Dr. Patel receives scientific advisory income from: Amgen, AstraZeneca, Bristol-Myers Squibb, Eli Lilly, Genentech, Illumina, Merck, Rakuten, Paradigm, Tempus. Dr. Patel's university receives research funding from: Bristol-Myers Squibb, Eli Lilly, Incyte, AstraZeneca/MedImmune, Merck, Pfizer, Roche/Genentech, Xcovery, Fate Therapeutics, Genocea, Iovance. Footnotes * Manuscript has been updated with additional analyses and co-authors

In this set of four phase 1 studies, a recombinant vesicular stomatitis virus (rVSV)–based Ebola vaccine induced Ebola virus–specific immune responses and was associated with side effects that included fever and transient arthritis, rash, and VSV viremia. In August 2014, after the outbreak of Ebola virus disease was declared a public health emergency of international concern by the World Health Organization (WHO), the Canadian government donated 800 vials of the replication-competent recombinant vesicular stomatitis virus (rVSV)–vectored Zaire ebolavirus (rVSV-ZEBOV) candidate vaccine to the WHO. The VSV Ebola Consortium (VEBCON) was created under the auspices of the WHO to initiate phase 1 studies to facilitate rapid progression to phase 2 and 3 trials in affected countries. 1 Live replicating viral vaccines elicit humoral and cellular immune responses against viral pathogens. 2 , 3 A single injection of 10 million plaque-forming units . . .