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The Drakesmith group investigated an unusual aspect of iron regulation against infection, and stumbled upon a new antiviral pathway

Natural Killer cells demonstrate distinct eQTL and transcriptome-wide disease associations, highlighting their role in autoimmunity.
Natural Killer cells are innate lymphocytes with central roles in immunosurveillance and are implicated in autoimmune pathogenesis. The degree to which regulatory variants affect Natural Killer cell gene expression is poorly understood. Here we perform expression quantitative trait locus mapping of negatively selected Natural Killer cells from a population of healthy Europeans (n = 245). We find a significant subset of genes demonstrate expression quantitative trait loci specific to Natural Killer cells and these are highly informative of human disease, in particular autoimmunity. A Natural Killer cell transcriptome-wide association study across five common autoimmune diseases identifies further novel associations at 27 genes. In addition to these cis observations, we find novel master-regulatory regions impacting expression of trans gene networks at regions including 19q13.4, the Killer cell Immunoglobulin-like Receptor region, GNLY, MC1R and UVSSA. Our findings provide new insights into the unique biology of Natural Killer cells, demonstrating markedly different expression quantitative trait loci from other immune cells, with implications for disease mechanisms.
Genetic determinants of monocyte splicing are enriched for disease susceptibility loci.
Insights into variation in monocyte context-specific splicing and transcript usage are limited. Here, we perform paired gene and transcript QTL mapping across distinct immune states using RNA sequencing data of monocytes isolated from a cohort of 185 healthy Europeans incubated alone or in the presence of interferon gamma (IFN-γ) or lipopolysaccharide (LPS). We identify regulatory variants for 5749 genes and 8727 transcripts, with 291 context-specific transcript QTL colocalizing with GWAS loci. Notable disease relevant associations include IFN-γ specific transcript QTL at COVID-19 severity locus rs10735079, where allelic variation modulates context-specific splicing of OAS1, and at rs4072037, a risk allele for gastro-esophageal cancer, which associates with context-specific splicing of MUC1. We use DNA methylation data from the same cells to demonstrate overlap between methylation QTL and causal context-specific expression QTL, permitting inference of the direction of effect. Finally, we identify a subset of expression QTL that uncouple genes from proximally acting regulatory networks, creating 'co-expression QTL' with different allele-specific correlation networks. Our findings highlight the interplay between context and genetics in the regulation of the monocyte gene expression and splicing, revealing putative mechanisms of diverse disease risk alleles including for COVID-19 and cancer.
Natural Killer cells demonstrate distinct eQTL and transcriptome-wide disease associations, highlighting their role in autoimmunity
Natural Killer (NK) cells are innate lymphocytes with central roles in immunosurveillance and are implicated in autoimmune pathogenesis. The degree to which regulatory variants affect NK gene expression is poorly understood. We performed expression quantitative trait locus (eQTL) mapping of negatively selected NK cells from a population of healthy Europeans (n=245). We find a significant subset of genes demonstrate eQTL specific to NK cells and these are highly informative of human disease, in particular autoimmunity. An NK cell transcriptome-wide association study (TWAS) across five common autoimmune diseases identified further novel associations at 27 genes. In addition to these cis observations, we find novel master-regulatory regions impacting expression of trans gene networks at regions including 19q13.4, the Killer cell Immunoglobulin-like Receptor (KIR) Region, GNLY and MC1R . Our findings provide new insights into the unique biology of NK cells, demonstrating markedly different eQTL from other immune cells, with implications for disease mechanisms.
Interferon-Gamma-Producing CD8+ Tissue Resident Memory T Cells Are a Targetable Hallmark of Immune Checkpoint Inhibitor-Colitis.
BACKGROUND & AIMS: The pathogenesis of immune checkpoint inhibitor (ICI)-colitis remains incompletely understood. We sought to identify key cellular drivers of ICI-colitis and their similarities to idiopathic ulcerative colitis, and to determine potential novel therapeutic targets. METHODS: We used a cross-sectional approach to study patients with ICI-colitis, those receiving ICI without the development of colitis, idiopathic ulcerative colitis, and healthy controls. A subset of patients with ICI-colitis were studied longitudinally. We applied a range of methods, including multiparameter and spectral flow cytometry, spectral immunofluorescence microscopy, targeted gene panels, and bulk and single-cell RNA sequencing. RESULTS: We demonstrate CD8+ tissue resident memory T (TRM) cells are the dominant activated T cell subset in ICI-colitis. The pattern of gastrointestinal immunopathology is distinct from ulcerative colitis at both the immune and epithelial-signaling levels. CD8+ TRM cell activation correlates with clinical and endoscopic ICI-colitis severity. Single-cell RNA sequencing analysis confirms activated CD8+ TRM cells express high levels of transcripts for checkpoint inhibitors and interferon-gamma in ICI-colitis. We demonstrate similar findings in both anti-CTLA-4/PD-1 combination therapy and in anti-PD-1 inhibitor-associated colitis. On the basis of our data, we successfully targeted this pathway in a patient with refractory ICI-colitis, using the JAK inhibitor tofacitinib. CONCLUSIONS: Interferon gamma-producing CD8+ TRM cells are a pathological hallmark of ICI-colitis and a novel target for therapy.
A common NFKB1 variant detected through antibody analysis in UK Biobank predicts risk of infection and allergy.
Infectious agents contribute significantly to the global burden of diseases through both acute infection and their chronic sequelae. We leveraged the UK Biobank to identify genetic loci that influence humoral immune response to multiple infections. From 45 genome-wide association studies in 9,611 participants from UK Biobank, we identified NFKB1 as a locus associated with quantitative antibody responses to multiple pathogens, including those from the herpes, retro-, and polyoma-virus families. An insertion-deletion variant thought to affect NFKB1 expression (rs28362491), was mapped as the likely causal variant and could play a key role in regulation of the immune response. Using 121 infection- and inflammation-related traits in 487,297 UK Biobank participants, we show that the deletion allele was associated with an increased risk of infection from diverse pathogens but had a protective effect against allergic disease. We propose that altered expression of NFKB1, as a result of the deletion, modulates hematopoietic pathways and likely impacts cell survival, antibody production, and inflammation. Taken together, we show that disruptions to the tightly regulated immune processes may tip the balance between exacerbated immune responses and allergy, or increased risk of infection and impaired resolution of inflammation.
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.
Distinct Transcriptional and Anti-Mycobacterial Profiles of Peripheral Blood Monocytes Dependent on the Ratio of Monocytes: Lymphocytes.
The ratio of monocytes and lymphocytes (ML ratio) in peripheral blood is associated with tuberculosis and malaria disease risk and cancer and cardiovascular disease outcomes. We studied anti-mycobacterial function and the transcriptome of monocytes in relation to the ML ratio. Mycobacterial growth inhibition assays of whole or sorted blood were performed and mycobacteria were enumerated by liquid culture. Transcriptomes of unstimulated CD14+ monocytes isolated by magnetic bead sorting were characterised by microarray. Transcript expression was tested for association with ML ratio calculated from leucocyte differential counts by linear regression. The ML ratio was associated with mycobacterial growth in vitro (β=2.23, SE 0.91, p=0.02). Using sorted monocytes and lymphocytes, in vivo ML ratio (% variance explained R2=11%, p=0.02) dominated over in vitro ratios (R2=5%, p=0.10) in explaining mycobacterial growth. Expression of 906 genes was associated with the ML ratio and 53 with monocyte count alone. ML-ratio associated genes were enriched for type-I and -II interferon signalling (p=1.2×10-8), and for genes under transcriptional control of IRF1, IRF2, RUNX1, RELA and ESRRB. The ML-ratio-associated gene set was enriched in TB disease (3.11-fold, 95% CI: 2.28-4.19, p=5.7×10-12) and other inflammatory diseases including atopy, HIV, IBD and SLE. The ML ratio is associated with distinct transcriptional and anti-mycobacterial profiles of monocytes that may explain the disease associations of the ML ratio.