XGR software for enhanced interpretation of genomic summary data, illustrated by application to immunological traits

Microarray analysis demonstrates up-regulation of the endothelin-1 gene with compensatory down-regulation of the ETA receptor gene in human portal vein

High blood pressure in the portal vein, portal hypertension (PH), is the final common pathway in liver cirrhosis regardless of aetiology. Complications from PH are the major cause of morbidity and mortality in these patients. Current drug therapy to reduce portal pressure is mainly limited to β-adrenergic receptor blockade but approximately 40% of patients do not respond. Our aim was to use microarray to measure the expression of ∼20,800 genes in portal vein from patients with PH undergoing transplantation for liver cirrhosis (PH, n=12) versus healthy vessels (control, n=9) to identify potential drug targets to improve therapy. Expression of 9,964 genes above background was detected in portal vein samples. Comparing PH veins versus control (adjusted P-value < 0.05, fold change > 1.5) identified 548 up-regulated genes and 1,996 down-regulated genes. The 2,544 differentially expressed genes were subjected to pathway analysis. We identified 49 significantly enriched pathways. The endothelin pathway was ranked the tenth most significant, the only vasoconstrictive pathway to be identified. ET-1 gene (EDN1) was significantly up-regulated, consistent with elevated levels of ET-1 peptide previously measured in PH and cirrhosis. ETA receptor gene (EDNRA) was significantly down-regulated, consistent with an adaptive response to increased peptide levels in the portal vein but there was no change in the ETB gene (EDNRB). The results provide further support for evaluating the efficacy of ETA receptor antagonists as a potential therapy in addition to β-blockers in patients with PH and cirrhosis.

eQTLs identify regulatory networks and drivers of variation in the individual response to sepsis

Sepsis is a clinical syndrome of life-threatening organ dysfunction caused by a dysregulated response to infection, for which disease heterogeneity is a major obstacle to developing targeted treatments. We have previously identified gene-expression-based patient subgroups (sepsis response signatures [SRS]) informative for outcome and underlying pathophysiology. Here, we aimed to investigate the role of genetic variation in determining the host transcriptomic response and to delineate regulatory networks underlying SRS. Using genotyping and RNA-sequencing data on 638 adult sepsis patients, we report 16,049 independent expression (eQTLs) and 32 co-expression module (modQTLs) quantitative trait loci in this disease context. We identified significant interactions between SRS and genotype for 1,578 SNP-gene pairs and combined transcription factor (TF) binding site information (SNP2TFBS) and predicted regulon activity (DoRothEA) to identify candidate upstream regulators. Overall, these approaches identified putative mechanistic links between host genetic variation, cell subtypes, and the individual transcriptomic response to infection.

A Novel Macrophage Subpopulation Conveys Increased Genetic Risk of Coronary Artery Disease

BACKGROUND

Coronary artery disease (CAD), the leading cause of death worldwide, is influenced by both environmental and genetic factors. Although over 250 genetic risk loci have been identified through genome-wide association studies, the specific causal variants and their regulatory mechanisms are still largely unknown, particularly in disease-relevant cell types such as macrophages.

METHODS

We utilized single-cell RNA-seq and single-cell multiomics approaches in primary human monocyte-derived macrophages to explore the transcriptional regulatory network involved in a critical pathogenic event of coronary atherosclerosis-the formation of lipid-laden foam cells. The relative genetic contribution to CAD was assessed by partitioning disease heritability across different macrophage subpopulations. Meta-analysis of single-cell RNA-seq data sets from 38 human atherosclerotic samples was conducted to provide high-resolution cross-referencing to macrophage subpopulations in vivo.

RESULTS

We identified 18 782 cis-regulatory elements by jointly profiling the gene expression and chromatin accessibility of >5000 macrophages. Integration with CAD genome-wide association study data prioritized 121 CAD-related genetic variants and 56 candidate causal genes. We showed that CAD heritability was not uniformly distributed and was particularly enriched in the gene programs of a novel CD52-hi lipid-handling macrophage subpopulation. These CD52-hi macrophages displayed significantly less lipoprotein accumulation and were also found in human atherosclerotic plaques. We investigated the cis-regulatory effect of a risk variant rs10488763 on FDX1, implicating the recruitment of AP-1 and C/EBP-β in the causal mechanisms at this locus.

CONCLUSIONS

Our results provide genetic evidence of the divergent roles of macrophage subsets in atherogenesis and highlight lipid-handling macrophages as a key subpopulation through which genetic variants operate to influence disease. These findings provide an unbiased framework for functional fine-mapping of genome-wide association study results using single-cell multiomics and offer new insights into the genotype-environment interactions underlying atherosclerotic disease.

High-throughput mass spectrometry maps the sepsis plasma proteome and differences in patient response

Sepsis, the dysregulated host response to infection causing life-threatening organ dysfunction, is a global health challenge requiring better understanding of pathophysiology and new therapeutic approaches. Here, we applied high-throughput tandem mass spectrometry to delineate the plasma proteome for sepsis and comparator groups (noninfected critical illness, postoperative inflammation, and healthy volunteers) involving 2612 samples (from 1611 patients) and 4553 liquid chromatography-mass spectrometry analyses acquired through a single batch of continuous measurements, with a throughput of 100 samples per day. We show how this scale of data can delineate proteins, pathways, and coexpression modules in sepsis and be integrated with paired leukocyte transcriptomic data (837 samples from n = 649 patients). We mapped the plasma proteomic landscape of the host response in sepsis, including changes over time, and identified features relating to etiology, clinical phenotypes (including organ failures), and severity. This work reveals subphenotypes informative for sepsis response state, disease processes, and outcome; identifies potential biomarkers; and advances opportunities for a precision medicine approach to sepsis.

Targeting IL-13 with tralokinumab normalizes type 2 inflammation in atopic dermatitis both early and at 2 years

BACKGROUND

Tralokinumab is a monoclonal antibody that specifically neutralizes interleukin (IL)-13, a key driver of skin inflammation and barrier abnormalities in atopic dermatitis (AD). This study evaluated early and 2-year impacts of IL-13 neutralization on skin and serum biomarkers following tralokinumab treatment in adults with moderate-to-severe AD.

METHODS

Skin biopsies and blood samples were evaluated from a subset of patients enrolled in the Phase 3 ECZTRA 1 (NCT03131648) and the long-term extension ECZTEND (NCT03587805) trials. Gene expression was assessed by RNA sequencing; protein expression was assessed by immunohistochemistry and immunoassay.

RESULTS

Tralokinumab improved the transcriptomic profile of lesional skin by Week 4. Mean improvements in the expression of genes dysregulated in AD were 39% at Week 16 and 85% at 2 years with tralokinumab, with 15% worsening at Week 16 with placebo. At Week 16, tralokinumab significantly decreased type 2 serum biomarkers (CCL17/TARC, periostin, and IgE), reduced epidermal thickness versus placebo, and increased loricrin coverage versus baseline. Two years of tralokinumab treatment significantly reduced expression of genes in the Th2 (IL4R, IL31, CCL17, and CCL26), Th1 (IFNG), and Th17/Th22 (IL22, S100A7, S100A8, and S100A9) pathways as well as increased expression of epidermal differentiation and barrier genes (CLDN1 and LOR). Tralokinumab also shifted atherosclerosis signaling pathway genes (SELE, IL-37, and S100A8) toward non-lesional expression.

CONCLUSION

Tralokinumab treatment improved epidermal pathology, reduced systemic markers of type 2 inflammation, and shifted expression of key AD biomarkers in skin towards non-lesional levels, further highlighting the key role of IL-13 in the pathogenesis of AD.

CLINICAL TRIAL REGISTRATION

NCT03131648, NCT03587805.

Transcriptomic evaluation of skin tape-strips in children with allergic asthma uncovers epidermal barrier dysfunction and asthma-associated biomarkers abnormalities

INTRODUCTION

Tape-strips, a minimally invasive method validated for the evaluation of several skin diseases, may help identify asthma-specific biomarkers in the skin of children with allergic asthma.

METHODS

Skin tape-strips were obtained and analyzed with RNA-Seq from children with moderate allergic asthma (MAA) (n = 11, mean age 7.00; SD = 1.67), severe allergic asthma (SAA) (n = 9, mean age 9.11; SD = 2.37), and healthy controls (HCs) (n = 12, mean age 7.36; SD = 2.03). Differentially expressed genes (DEGs) were identified by fold change ≥2 with a false discovery rate <0.05. Transcriptomic biomarkers were analyzed for their accuracy in distinguishing asthma from HCs, their relationships with asthma-related outcomes (exacerbation rate, lung function-FEV1, IOS-R5-20, and lung inflammation-FeNO), and their links to skin (barrier and immune response) and lung (remodeling, metabolism, aging) pathogenetic pathways.

RESULTS

RNA-Seq captured 1113 in MAA and 2117 DEGs in SAA. Epidermal transcriptomic biomarkers for terminal differentiation (FLG/filaggrin), cell adhesion (CDH19, JAM2), lipid biosynthesis/metabolism (ACOT2, LOXL2) were significantly downregulated. Gene set variation analysis revealed enrichment of Th1/IFNγ pathways (p < .01). MAA and SAA shared downregulation of G-protein-coupled receptor (OR4A16, TAS1R3), upregulation of TGF-β/ErbB signaling-related (ACVR1B, EGFR, ID1/2), and upregulation of mitochondrial-related (HIGD2A, VDAC3, NDUFB9) genes. Skin transcriptomic biomarkers correlated with the annualized exacerbation rate and with lung function parameters. A two-gene classifier (TSSC4-FAM212B) was able to differentiate asthma from HCs with 100% accuracy.

CONCLUSION

Tape-strips detected epithelial barrier and asthma-associated signatures in normal-appearing skin from children with allergic asthma and may serve as an alternative to invasive approaches for evaluating asthma endotypes.

Patient stratification using plasma cytokines and their regulators in sepsis: relationship to outcomes, treatment effect and leucocyte transcriptomic subphenotypes

RATIONALE

Heterogeneity of the host response within sepsis, acute respiratory distress syndrome (ARDS) and more widely critical illness, limits discovery and targeting of immunomodulatory therapies. Clustering approaches using clinical and circulating biomarkers have defined hyper-inflammatory and hypo-inflammatory subphenotypes in ARDS associated with differential treatment response. It is unknown if similar subphenotypes exist in sepsis populations where leucocyte transcriptomic-defined subphenotypes have been reported.

OBJECTIVES

We investigated whether inflammatory clusters based on cytokine protein abundance were seen in sepsis, and the relationships with previously described transcriptomic subphenotypes.

METHODS

Hierarchical cluster and latent class analysis were applied to an observational study (UK Genomic Advances in Sepsis (GAinS)) (n=124 patients) and two clinical trial datasets (VANISH, n=155 and LeoPARDS, n=484) in which the plasma protein abundance of 65, 21, 11 circulating cytokines, cytokine receptors and regulators were quantified. Clinical features, outcomes, response to trial treatments and assignment to transcriptomic subphenotypes were compared between inflammatory clusters.

MEASUREMENTS AND MAIN RESULTS

We identified two (UK GAinS, VANISH) or three (LeoPARDS) inflammatory clusters. A group with high levels of pro-inflammatory and anti-inflammatory cytokines was seen that was associated with worse organ dysfunction and survival. No interaction between inflammatory clusters and trial treatment response was found. We found variable overlap of inflammatory clusters and leucocyte transcriptomic subphenotypes.

CONCLUSIONS

These findings demonstrate that differences in response at the level of cytokine biology show clustering related to severity, but not treatment response, and may provide complementary information to transcriptomic sepsis subphenotypes.

TRIAL REGISTRATION NUMBER

ISRCTN20769191, ISRCTN12776039.

Single-cell analysis of bronchoalveolar cells in inflammatory and fibrotic post-COVID lung disease

Background

Persistent radiological lung abnormalities are evident in many survivors of acute coronavirus disease 2019 (COVID-19). Consolidation and ground glass opacities are interpreted to indicate subacute inflammation whereas reticulation is thought to reflect fibrosis. We sought to identify differences at molecular and cellular level, in the local immunopathology of post-COVID inflammation and fibrosis.

Methods

We compared single-cell transcriptomic profiles and T cell receptor (TCR) repertoires of bronchoalveolar cells obtained from convalescent individuals with each radiological pattern, targeting lung segments affected by the predominant abnormality.

Results

CD4 central memory T cells and CD8 effector memory T cells were significantly more abundant in those with inflammatory radiology. Clustering of similar TCRs from multiple donors was a striking feature of both phenotypes, consistent with tissue localised antigen-specific immune responses. There was no enrichment for known SARS-CoV-2-reactive TCRs, raising the possibility of T cell-mediated immunopathology driven by failure in immune self-tolerance.

Conclusions

Post-COVID radiological inflammation and fibrosis show evidence of shared antigen-specific T cell responses, suggesting a role for therapies targeting T cells in limiting post-COVID lung damage.

Characterization of the genetic determinants of context-specific DNA methylation in primary monocytes

To better understand inter-individual variation in sensitivity of DNA methylation (DNAm) to immune activity, we characterized effects of inflammatory stimuli on primary monocyte DNAm (n = 190). We find that monocyte DNAm is site-dependently sensitive to lipopolysaccharide (LPS), with LPS-induced demethylation occurring following hydroxymethylation. We identify 7,359 high-confidence immune-modulated CpGs (imCpGs) that differ in genomic localization and transcription factor usage according to whether they represent a gain or loss in DNAm. Demethylated imCpGs are profoundly enriched for enhancers and colocalize to genes enriched for disease associations, especially cancer. DNAm is age associated, and we find that 24-h LPS exposure triggers approximately 6 months of gain in epigenetic age, directly linking epigenetic aging with innate immune activity. By integrating LPS-induced changes in DNAm with genetic variation, we identify 234 imCpGs under local genetic control. Exploring shared causal loci between LPS-induced DNAm responses and human disease traits highlights examples of disease-associated loci that modulate imCpG formation.

A cross-disease, pleiotropy-driven approach for therapeutic target prioritization and evaluation

Cross-disease genome-wide association studies (GWASs) unveil pleiotropic loci, mostly situated within the non-coding genome, each of which exerts pleiotropic effects across multiple diseases. However, the challenge "W-H-W" (namely, whether, how, and in which specific diseases pleiotropy can inform clinical therapeutics) calls for effective and integrative approaches and tools. We here introduce a pleiotropy-driven approach specifically designed for therapeutic target prioritization and evaluation from cross-disease GWAS summary data, with its validity demonstrated through applications to two systems of disorders (neuropsychiatric and inflammatory). We illustrate its improved performance in recovering clinical proof-of-concept therapeutic targets. Importantly, it identifies specific diseases where pleiotropy informs clinical therapeutics. Furthermore, we illustrate its versatility in accomplishing advanced tasks, including pathway crosstalk identification and downstream crosstalk-based analyses. To conclude, our integrated solution helps bridge the gap between pleiotropy studies and therapeutics discovery.

Tape strips detect molecular alterations and cutaneous biomarkers in skin of patients with hidradenitis suppurativa

BACKGROUND

Hidradenitis suppurativa (HS) has a high unmet need for better treatments. Biopsies are considered the gold standard for studying molecular alterations in skin. A reproducible, minimally invasive approach is needed for longitudinal monitoring in trials and in pediatric populations.

OBJECTIVE

To determine whether skin tape strips can detect molecular alterations in HS and identify biomarkers of disease activity.

METHODS

We performed RNA sequencing on tape strips collected from lesional and healthy-appearing (nonlesional) HS skin (n = 22) and healthy controls (n = 21). We correlated the expression of skin biomarkers between tape strips and a previously published gene-signature of HS biopsies.

RESULTS

Tape strips detected upregulation of known HS biomarkers (eg, Interleukin[IL]-17A) in nonlesional and/or lesional skin and also identified novel clinically actionable targets, including OX40 and JAK3. The expression of Th17 and tumor necrosis factor-α pathways were highly correlated between tape strips and biopsies. HS clinical severity was significantly associated with expression of biomarkers (eg tumor necrosis factor-α , IL-17 A/F, OX40, JAK1-3, IL-4R) in HS lesional and/or nonlesional skin.

LIMITATIONS

Sample size. Tape stripping is limited in depth.

CONCLUSION

This study validates tape strips as a minimally-invasive approach to identify cutaneous biomarkers in HS. This provides a novel avenue for monitoring treatment efficacy and a potential step toward individualized therapy in HS.

Sclerotic-Type Cutaneous Chronic Graft-Versus-Host Disease Exhibits Activation of T Helper 1 and OX40 Cytokines

Sclerotic-type cutaneous chronic graft-versus-host disease is a severe complication of allogeneic hematopoietic stem cell transplantation, with profound morbidity. A dearth of effective, targeted treatment options necessitates further investigation into the molecular mechanisms underlying this T-cell-mediated disease. In this study, we compared the transcriptome in skin biopsies from pediatric and young adult (aged <25 years) patients with sclerotic-type cutaneous chronic graft-versus-host disease (n = 7) with that in demographically matched healthy controls (n = 8) and patients with atopic dermatitis (n = 10) using RNA sequencing with RT-PCR and immunohistochemistry validation. Differential expression was defined as fold change > 1.5 and false discovery rate < 0.05. Sclerotic-type cutaneous chronic graft-versus-host disease exhibited strong and significant T helper (Th)1 skewing through key related cytokines and chemokines (CXCL9/10/11, IFNG/IFN-γ, STAT1/signal transducer and activator of transcription 1). Several markers related to the TSLP-OX40 axis were significantly upregulated relative to those in both controls and lesional atopic dermatitis, including TNFSF4/OX40L, TSLP, and IL33, as well as fibroinflammatory signatures characterized in a prior study in systemic sclerosis. Gene set variation analysis reflected marker-level findings, showing the greatest enrichment of the Th1 and fibroinflammatory pathways, with no global activation identified in Th2 or Th17/Th22. Cell-type deconvolution revealed a significant representation of macrophages and vascular endothelial cells. Sclerotic-type cutaneous chronic graft-versus-host disease in young patients may therefore be characterized by strong Th1-related upregulation with a unique TSLP-OX40 signature, suggesting new therapeutic avenues for this devastating disease.

Priority index for critical Covid-19 identifies clinically actionable targets and drugs

While genome-wide studies have identified genomic loci in hosts associated with life-threatening Covid-19 (critical Covid-19), the challenge of resolving these loci hinders further identification of clinically actionable targets and drugs. Building upon our previous success, we here present a priority index solution designed to address this challenge, generating the target and drug resource that consists of two indexes: the target index and the drug index. The primary purpose of the target index is to identify clinically actionable targets by prioritising genes associated with Covid-19. We illustrate the validity of the target index by demonstrating its ability to identify pre-existing Covid-19 phase-III drug targets, with the majority of these targets being found at the leading prioritisation (leading targets). These leading targets have their evolutionary origins in Amniota ('four-leg vertebrates') and are predominantly involved in cytokine-cytokine receptor interactions and JAK-STAT signaling. The drug index highlights opportunities for repurposing clinically approved JAK-STAT inhibitors, either individually or in combination. This proposed strategic focus on the JAK-STAT pathway is supported by the active pursuit of therapeutic agents targeting this pathway in ongoing phase-II/III clinical trials for Covid-19.

Rare loss-of-function variants in matrisome genes are enriched in Ebstein's anomaly

Ebstein's anomaly, a rare congenital heart disease, is distinguished by the failure of embryological delamination of the tricuspid valve leaflets from the underlying primitive right ventricle myocardium. Gaining insight into the genetic basis of Ebstein's anomaly allows a more precise definition of its pathogenesis. In this study, two distinct cohorts from the Chinese Han population were included: a case-control cohort consisting of 82 unrelated cases and 125 controls without cardiac phenotypes and a trio cohort comprising 36 parent-offspring trios. Whole-exome sequencing data from all 315 participants were utilized to identify qualifying variants, encompassing rare (minor allele frequency < 0.1% from East Asians in the gnomAD database) functional variants and high-confidence (HC) loss-of-function (LoF) variants. Various statistical models, including burden tests and variance-component models, were employed to identify rare variants, genes, and biological pathways associated with Ebstein's anomaly. Significant associations were noted between Ebstein's anomaly and rare HC LoF variants found in genes related to the matrisome, a collection of extracellular matrix (ECM) components. Specifically, 47 genes with HC LoF variants were exclusively or predominantly identified in cases, while nine genes showed such variants in the probands. Over half of unrelated cases (n = 42) and approximately one-third of probands (n = 12) were found to carry one or two LoF variants in these prioritized genes. These results highlight the role of the matrisome in the pathogenesis of Ebstein's anomaly, contributing to a better understanding of the genetic architecture underlying this condition. Our findings hold the potential to impact the genetic diagnosis and treatment approaches for Ebstein's anomaly.

Laser capture microdissection provides a novel molecular profile of human primary cutaneous melanoma

Melanoma accounts for the majority of skin cancer-related mortality, highlighting the need to better understand melanoma initiation and progression. In-depth molecular analysis of neoplastic melanocytes in whole tissue biopsies may be diluted by inflammatory infiltration, which may obscure gene signatures specific to neoplastic cells. Thus, a method is needed to precisely uncover molecular changes specific to tumor cells from a limited sample of primary melanomas. Here, we performed laser capture microdissection (LCM) and gene expression profiling of patient-derived frozen sections of pigmented lesions and primary cutaneous melanoma. Compared to bulk tissue analysis, analysis of LCM-derived samples identified 9528 additional differentially expressed genes (DEGs) including melanocyte-specific genes like PMEL and TYR, with enriched of pathways related to cell proliferation. LCM methodology also identified potentially targetable kinases specific to melanoma cells that were not detected by bulk tissue analysis. Taken together, our data demonstrate that there are marked differences in gene expression profiles depending on the method of sample isolation. We found that LCM captured higher expression of melanoma-related genes while whole tissue biopsy identified a wider range of inflammatory markers. Taken together, our data demonstrate that LCM is a valid approach to identify melanoma-specific changes using a relatively small amount of primary patient-derived melanoma sample.

Analysis of reproducibility and robustness of a renal proximal tubule microphysiological system OrganoPlate 3-lane 40 for in vitro studies of drug transport and toxicity

Microphysiological systems are an emerging area of in vitro drug development, and their independent evaluation is important for wide adoption and use. The primary goal of this study was to test reproducibility and robustness of a renal proximal tubule microphysiological system, OrganoPlate 3-lane 40, as an in vitro model for drug transport and toxicity studies. This microfluidic model was compared with static multiwell cultures and tested using several human renal proximal tubule epithelial cell (RPTEC) types. The model was characterized in terms of the functional transport for various tubule-specific proteins, epithelial permeability of small molecules (cisplatin, tenofovir, and perfluorooctanoic acid) versus large molecules (fluorescent dextrans, 60-150 kDa), and gene expression response to a nephrotoxic xenobiotic. The advantages offered by OrganoPlate 3-lane 40 as compared with multiwell cultures are the presence of media flow, albeit intermittent, and increased throughput compared with other microfluidic models. However, OrganoPlate 3-lane 40 model appeared to offer only limited (eg, MRP-mediated transport) advantages in terms of either gene expression or functional transport when compared with the multiwell plate culture conditions. Although OrganoPlate 3-lane 40 can be used to study cellular uptake and direct toxic effects of small molecules, it may have limited utility for drug transport studies. Overall, this study offers refined experimental protocols and comprehensive comparative data on the function of RPETCs in traditional multiwell culture and microfluidic OrganoPlate 3-lane 40, information that will be invaluable for the prospective end-users of in vitro models of the human proximal tubule.

Mapping the epigenomic landscape of human monocytes following innate immune activation reveals context-specific mechanisms driving endotoxin tolerance

BACKGROUND

Monocytes are key mediators of innate immunity to infection, undergoing profound and dynamic changes in epigenetic state and immune function which are broadly protective but may be dysregulated in disease. Here, we aimed to advance understanding of epigenetic regulation following innate immune activation, acutely and in endotoxin tolerant states.

METHODS

We exposed human primary monocytes from healthy donors (n = 6) to interferon-γ or differing combinations of endotoxin (lipopolysaccharide), including acute response (2 h) and two models of endotoxin tolerance: repeated stimulations (6 + 6 h) and prolonged exposure to endotoxin (24 h). Another subset of monocytes was left untreated (naïve). We identified context-specific regulatory elements based on epigenetic signatures for chromatin accessibility (ATAC-seq) and regulatory non-coding RNAs from total RNA sequencing.

RESULTS

We present an atlas of differential gene expression for endotoxin and interferon response, identifying widespread context specific changes. Across assayed states, only 24-29% of genes showing differential exon usage are also differential at the gene level. Overall, 19.9% (6,884 of 34,616) of repeatedly observed ATAC peaks were differential in at least one condition, the majority upregulated on stimulation and located in distal regions (64.1% vs 45.9% of non-differential peaks) within which sequences were less conserved than non-differential peaks. We identified enhancer-derived RNA signatures specific to different monocyte states that correlated with chromatin accessibility changes. The endotoxin tolerance models showed distinct chromatin accessibility and transcriptomic signatures, with integrated analysis identifying genes and pathways involved in the inflammatory response, detoxification, metabolism and wound healing. We leveraged eQTL mapping for the same monocyte activation states to link potential enhancers with specific genes, identifying 1,946 unique differential ATAC peaks with 1,340 expression associated genes. We further use this to inform understanding of reported GWAS, for example involving FCHO1 and coronary artery disease.

CONCLUSION

This study reports context-specific regulatory elements based on transcriptomic profiling and epigenetic signatures for enhancer-derived RNAs and chromatin accessibility in immune tolerant monocyte states, and demonstrates the informativeness of linking such elements and eQTL to inform future mechanistic studies aimed at defining therapeutic targets of immunosuppression and diseases.

Multi-tissue transcriptomic and serum metabolomic assessment reveals systemic implications of acute ozone-induced stress response in male Wistar Kyoto rats

Air pollutant exposures have been linked to systemic disease; however, the underlying mechanisms between responses of the target tissue and systemic effects are poorly understood. A prototypic inducer of stress, ozone causes respiratory and systemic multiorgan effects through activation of a neuroendocrine stress response. The goal of this study was to assess transcriptomic signatures of multiple tissues and serum metabolomics to understand how neuroendocrine and adrenal-derived stress hormones contribute to multiorgan health outcomes. Male Wistar Kyoto rats (12-13 weeks old) were exposed to filtered air or 0.8 ppm ozone for 4-hours, and blood/tissues were collected immediately post-exposure. Each tissue had distinct expression profiles at baseline. Ozone changed 1,640 genes in lung, 274 in hypothalamus, 2,516 in adrenals, 1,333 in liver, 1,242 in adipose, and 5,102 in muscle (adjusted p-value < 0.1, absolute fold-change > 50%). Serum metabolomic analysis identified 863 metabolites, of which 447 were significantly altered in ozone-exposed rats (adjusted p-value < 0.1, absolute fold change > 20%). A total of 6 genes were differentially expressed in all 6 tissues. Glucocorticoid signaling, hypoxia, and GPCR signaling were commonly changed, but ozone induced tissue-specific changes in oxidative stress, immune processes, and metabolic pathways. Genes upregulated by TNF-mediated NFkB signaling were differentially expressed in all ozone-exposed tissues, but those defining inflammatory response were tissue-specific. Upstream predictor analysis identified common mediators of effects including glucocorticoids, although the specific genes responsible for these predictors varied by tissue. Metabolomic analysis showed major changes in lipids, amino acids, and metabolites linked to the gut microbiome, concordant with transcriptional changes identified through pathway analysis within liver, muscle, and adipose tissues. The distribution of receptors and transcriptional mechanisms underlying the ozone-induced stress response are tissue-specific and involve induction of unique gene networks and metabolic phenotypes, but the shared initiating triggers converge into shared pathway-level responses. This multi-tissue transcriptomic analysis, combined with circulating metabolomic assessment, allows characterization of the systemic inhaled pollutant-induced stress response.

Priority index for asthma (PIA): In silico discovery of shared and distinct drug targets for adult- and childhood-onset disease

Asthma is a chronic disease that is caused by a combination of genetic risks and environmental triggers and can affect both adults and children. Genome-wide association studies have revealed partly distinct genetic architectures for its two age-of-onset subtypes (namely, adult-onset and childhood-onset). We reason that identifying shared and distinct drug targets between these subtypes may inform the development of subtype-specific therapeutic strategies. In attempting this, we here introduce Priority Index for Asthma or PIA, a genetics-led and network-driven drug target prioritisation tool for asthma. We demonstrate the validity of the tool in improving drug target prioritisation for asthma compared to the status quo methods, as well as in capturing the underlying etiology and existing therapeutics for the disease. We also illustrate how PIA can be used to prioritise drug targets for adult- and childhood-onset asthma, as well as to identify shared and distinct pathway crosstalk genes. Shared crosstalk genes are mostly involved in JAK-STAT signaling, with clinical evidence supporting that targeting this pathway may be a promising drug repurposing opportunity for both subtypes. Crosstalk genes specific to childhood-onset asthma are enriched for PI3K-AKT-mTOR signaling, and we identify genes that are already targeted by licensed medications as repurposed drug candidates for this subtype. We make all our results accessible and reproducible at http://www.genetictargets.com/PIA. Collectively, our study has significant implications for asthma computational medicine research and can guide the future development of subtype-specific therapeutic strategies for the disease.

The dcGO Domain-Centric Ontology Database in 2023: New Website and Extended Annotations for Protein Structural Domains

Protein structural domains have been less studied than full-length proteins in terms of ontology annotations. The dcGO database has filled this gap by providing mappings from protein domains to ontologies. The dcGO update in 2023 extends annotations for protein domains of multiple definitions (SCOP, Pfam, and InterPro) with commonly used ontologies that are categorised into functions, phenotypes, diseases, drugs, pathways, regulators, and hallmarks. This update adds new dimensions to the utility of both ontology and protein domain resources. A newly designed website at http://www.protdomainonto.pro/dcGO offers a more centralised and user-friendly way to access the dcGO database, with enhanced faceted search returning term- and domain-specific information pages. Users can navigate both ontology terms and annotated domains through improved ontology hierarchy browsing. A newly added facility enables domain-based ontology enrichment analysis.

Ten quick tips for avoiding pitfalls in multi-omics data integration analyses

Data are the most important elements of bioinformatics: Computational analysis of bioinformatics data, in fact, can help researchers infer new knowledge about biology, chemistry, biophysics, and sometimes even medicine, influencing treatments and therapies for patients. Bioinformatics and high-throughput biological data coming from different sources can even be more helpful, because each of these different data chunks can provide alternative, complementary information about a specific biological phenomenon, similar to multiple photos of the same subject taken from different angles. In this context, the integration of bioinformatics and high-throughput biological data gets a pivotal role in running a successful bioinformatics study. In the last decades, data originating from proteomics, metabolomics, metagenomics, phenomics, transcriptomics, and epigenomics have been labelled -omics data, as a unique name to refer to them, and the integration of these omics data has gained importance in all biological areas. Even if this omics data integration is useful and relevant, due to its heterogeneity, it is not uncommon to make mistakes during the integration phases. We therefore decided to present these ten quick tips to perform an omics data integration correctly, avoiding common mistakes we experienced or noticed in published studies in the past. Even if we designed our ten guidelines for beginners, by using a simple language that (we hope) can be understood by anyone, we believe our ten recommendations should be taken into account by all the bioinformaticians performing omics data integration, including experts.

Comprehensive epigenomic profiling reveals the extent of disease-specific chromatin states and informs target discovery in ankylosing spondylitis

Ankylosing spondylitis (AS) is a common, highly heritable inflammatory arthritis characterized by enthesitis of the spine and sacroiliac joints. Genome-wide association studies (GWASs) have revealed more than 100 genetic associations whose functional effects remain largely unresolved. Here, we present a comprehensive transcriptomic and epigenomic map of disease-relevant blood immune cell subsets from AS patients and healthy controls. We find that, while CD14⁺ monocytes and CD4⁺ and CD8⁺ T cells show disease-specific differences at the RNA level, epigenomic differences are only apparent upon multi-omics integration. The latter reveals enrichment at disease-associated loci in monocytes. We link putative functional SNPs to genes using high-resolution Capture-C at 10 loci, including PTGER4 and ETS1, and show how disease-specific functional genomic data can be integrated with GWASs to enhance therapeutic target discovery. This study combines epigenetic and transcriptional analysis with GWASs to identify disease-relevant cell types and gene regulation of likely pathogenic relevance and prioritize drug targets.

A tiered testing strategy based on in vitro phenotypic and transcriptomic data for selecting representative petroleum UVCBs for toxicity evaluation in vivo

Hazard evaluation of substances of "unknown or variable composition, complex reaction products and biological materials" (UVCBs) remains a major challenge in regulatory science because their chemical composition is difficult to ascertain. Petroleum substances are representative UVCBs and human cell-based data have been previously used to substantiate their groupings for regulatory submissions. We hypothesized that a combination of phenotypic and transcriptomic data could be integrated to make decisions as to selection of group-representative worst-case petroleum UVCBs for subsequent toxicity evaluation in vivo. We used data obtained from 141 substances from 16 manufacturing categories previously tested in 6 human cell types (induced pluripotent stem cell [iPSC]-derived hepatocytes, cardiomyocytes, neurons, and endothelial cells, and MCF7 and A375 cell lines). Benchmark doses for gene-substance combinations were calculated, and both transcriptomic and phenotype-derived points of departure (PODs) were obtained. Correlation analysis and machine learning were used to assess associations between phenotypic and transcriptional PODs and to determine the most informative cell types and assays, thus representing a cost-effective integrated testing strategy. We found that 2 cell types-iPSC-derived-hepatocytes and -cardiomyocytes-contributed the most informative and protective PODs and may be used to inform selection of representative petroleum UVCBs for further toxicity evaluation in vivo. Overall, although the use of new approach methodologies to prioritize UVCBs has not been widely adopted, our study proposes a tiered testing strategy based on iPSC-derived hepatocytes and cardiomyocytes to inform selection of representative worst-case petroleum UVCBs from each manufacturing category for further toxicity evaluation in vivo.

Proteomic characterization of atopic dermatitis blood from infancy to adulthood

BACKGROUND

Patients with atopic dermatitis (AD) have systemic biomarker dysregulation that differs by age group; however, the proteomic characteristics of these age-based changes are unknown.

OBJECTIVE

To profile blood proteins of patients with AD across different age groups versus age-appropriate controls.

METHODS

Using the Olink high-throughput proteomic platform, we profiled 375 serum proteins of 20 infants (age, 0-5 years), 39 children (age, 6-11 years), 21 adolescents (age, 12-17 years), and 20 adults (age, ≥18 years) with moderate-to-severe AD and 83 age-appropriate controls.

RESULTS

Each group presented a distinct systemic proteomic signature. Th2-related proteins were increased in infant AD and further intensified with age through adolescence and adulthood (interleukin 4/CCL13/CCL17). In contrast, Th1 axis down-regulation was detected in infants with AD and gradually reversed to increased Th1 products (interferon γ/CXCL9/CXCL10/CCL2) in patients with AD from childhood to adulthood. Despite their short disease duration, infants already had evidence of systemic inflammation, with significant upregulation of innate immunity (interleukin 17C/ interleukin-1RN), T-cell activation/migration (CCL19), Th2 (CCL13/CCL17), and Th17 (PI3) proteins. Adults with AD present unique upregulation of cardiovascular proteins related to coagulation and diabetes.

LIMITATIONS

Cross-sectional observational study with a single time point.

CONCLUSION

Systemic immune signatures of AD are age-specific beyond the shared Th2 immune activation. These data advocate for precision medicine approaches based on age-specific AD profiles.

Prior anti-CTLA-4 therapy impacts molecular characteristics associated with anti-PD-1 response in advanced melanoma

Immune checkpoint inhibitors (ICIs), including CTLA-4- and PD-1-blocking antibodies, can have profound effects on tumor immune cell infiltration that have not been consistent in biopsy series reported to date. Here, we analyze seven molecular datasets of samples from patients with advanced melanoma (N = 514) treated with ICI agents to investigate clinical, genomic, and transcriptomic features of anti-PD-1 response in cutaneous melanoma. We find that prior anti-CTLA-4 therapy is associated with differences in genomic, individual gene, and gene signatures in anti-PD-1 responders. Anti-CTLA-4-experienced melanoma tumors that respond to PD-1 blockade exhibit increased tumor mutational burden, inflammatory signatures, and altered cell cycle processes compared with anti-CTLA-4-naive tumors or anti-CTLA-4-experienced, anti-PD-1-nonresponsive melanoma tumors. We report a harmonized, aggregate resource and suggest that prior CTLA-4 blockade therapy is associated with marked differences in the tumor microenvironment that impact the predictive features of PD-1 blockade therapy response.

Inducible apelin receptor knockdown reduces differentiation efficiency and contractility of hESC-derived cardiomyocytes

AIMS

The apelin receptor, a G protein-coupled receptor, has emerged as a key regulator of cardiovascular development, physiology, and disease. However, there is a lack of suitable human in vitro models to investigate the apelinergic system in cardiovascular cell types. For the first time we have used human embryonic stem cell-derived cardiomyocytes (hESC-CMs) and a novel inducible knockdown system to examine the role of the apelin receptor in both cardiomyocyte development and to determine the consequences of loss of apelin receptor function as a model of disease.

METHODS AND RESULTS

Expression of the apelin receptor and its ligands in hESCs and hESC-CMs was determined. hESCs carrying a tetracycline-inducible short hairpin RNA targeting the apelin receptor were generated using the sOPTiKD system. Phenotypic assays characterized the consequences of either apelin receptor knockdown before hESC-CM differentiation (early knockdown) or in 3D engineered heart tissues as a disease model (late knockdown). hESC-CMs expressed the apelin signalling system at a similar level to the adult heart. Early apelin receptor knockdown decreased cardiomyocyte differentiation efficiency and prolonged voltage sensing, associated with asynchronous contraction. Late apelin receptor knockdown had detrimental consequences on 3D engineered heart tissue contractile properties, decreasing contractility and increasing stiffness.

CONCLUSIONS

We have successfully knocked down the apelin receptor, using an inducible system, to demonstrate a key role in hESC-CM differentiation. Knockdown in 3D engineered heart tissues recapitulated the phenotype of apelin receptor down-regulation in a failing heart, providing a potential platform for modelling heart failure and testing novel therapeutic strategies.

Klarigi: Characteristic explanations for semantic biomedical data

Annotation of biomedical entities with ontology classes provides for formal semantic analysis and mobilisation of background knowledge in determining their relationships. To date, enrichment analysis has been routinely employed to identify classes that are over-represented in annotations across sets of groups, such as biosample gene expression profiles or patient phenotypes, and is useful for a range of tasks including differential diagnosis and causative variant prioritisation. These approaches, however, usually consider only univariate relationships, make limited use of the semantic features of ontologies, and provide limited information and evaluation of the explanatory power of both singular and grouped candidate classes. Moreover, they are not designed to solve the problem of deriving cohesive, characteristic, and discriminatory sets of classes for entity groups. We have developed a new tool, called Klarigi, which introduces multiple scoring heuristics for identification of classes that are both compositional and discriminatory for groups of entities annotated with ontology classes. The tool includes a novel algorithm for derivation of multivariable semantic explanations for entity groups, makes use of semantic inference through live use of an ontology reasoner, and includes a classification method for identifying the discriminatory power of candidate sets, in addition to significance testing apposite to traditional enrichment approaches. We describe the design and implementation of Klarigi, including its scoring and explanation determination methods, and evaluate its use in application to two test cases with clinical significance, comparing and contrasting methods and results with literature-based and enrichment analysis methods. We demonstrate that Klarigi produces characteristic and discriminatory explanations for groups of biomedical entities in two settings. We also show that these explanations recapitulate and extend the knowledge held in existing biomedical databases and literature for several diseases. We conclude that Klarigi provides a distinct and valuable perspective on biomedical datasets when compared with traditional enrichment methods, and therefore constitutes a new method by which biomedical datasets can be explored, contributing to improved insight into semantic data.

When cancer drug resistance meets metabolomics (bulk, single-cell and/or spatial): Progress, potential, and perspective

Resistance to drug treatment is a critical barrier in cancer therapy. There is an unmet need to explore cancer hallmarks that can be targeted to overcome this resistance for therapeutic gain. Over time, metabolic reprogramming has been recognised as one hallmark that can be used to prevent therapeutic resistance. With the advent of metabolomics, targeting metabolic alterations in cancer cells and host patients represents an emerging therapeutic strategy for overcoming cancer drug resistance. Driven by technological and methodological advances in mass spectrometry imaging, spatial metabolomics involves the profiling of all the metabolites (metabolomics) so that the spatial information is captured bona fide within the sample. Spatial metabolomics offers an opportunity to demonstrate the drug-resistant tumor profile with metabolic heterogeneity, and also poses a data-mining challenge to reveal meaningful insights from high-dimensional spatial information. In this review, we discuss the latest progress, with the focus on currently available bulk, single-cell and spatial metabolomics technologies and their successful applications in pre-clinical and translational studies on cancer drug resistance. We provide a summary of metabolic mechanisms underlying cancer drug resistance from different aspects; these include the Warburg effect, altered amino acid/lipid/drug metabolism, generation of drug-resistant cancer stem cells, and immunosuppressive metabolism. Furthermore, we propose solutions describing how to overcome cancer drug resistance; these include early detection during cancer initiation, monitoring of clinical drug response, novel anticancer drug and target metabolism, immunotherapy, and the emergence of spatial metabolomics. We conclude by describing the perspectives on how spatial omics approaches (integrating spatial metabolomics) could be further developed to improve the management of drug resistance in cancer patients.

Shared genetic architecture of hernias: A genome-wide association study with multivariable meta-analysis of multiple hernia phenotypes

Abdominal hernias are common and characterised by the abnormal protrusion of a viscus through the wall of the abdominal cavity. The global incidence is 18.5 million annually and there are limited non-surgical treatments. To improve understanding of common hernia aetiopathology, we performed a six-stage genome-wide association study (GWAS) of 62,637 UK Biobank participants with either single or multiple hernia phenotypes including inguinal, femoral, umbilical and hiatus hernia. Additionally, we performed multivariable meta-analysis with metaUSAT, to allow integration of summary data across traits to generate combined effect estimates. On individual hernia analysis, we identified 3404 variants across 38 genome-wide significant (p < 5×10-8) loci of which 11 are previously unreported. Robust evidence for five shared susceptibility loci was discovered: ZC3H11B, EFEMP1, MHC region, WT1 and CALD1. Combined hernia phenotype analyses with additional multivariable meta-analysis of summary statistics in metaUSAT revealed 28 independent (seven previously unreported) shared susceptibility loci. These clustered in functional categories related to connective tissue and elastic fibre homeostasis. Weighted genetic risk scores also correlated with disease severity suggesting a phenotypic-genotypic severity correlation, an important finding to inform future personalised therapeutic approaches to hernia.

Transcriptional reprogramming from innate immune functions to a pro-thrombotic signature by monocytes in COVID-19

Although alterations in myeloid cells have been observed in COVID-19, the specific underlying mechanisms are not completely understood. Here, we examine the function of classical CD14+ monocytes in patients with mild and moderate COVID-19 during the acute phase of infection and in healthy individuals. Monocytes from COVID-19 patients display altered expression of cell surface receptors and a dysfunctional metabolic profile that distinguish them from healthy monocytes. Secondary pathogen sensing ex vivo leads to defects in pro-inflammatory cytokine and type-I IFN production in moderate COVID-19 cases, together with defects in glycolysis. COVID-19 monocytes switch their gene expression profile from canonical innate immune to pro-thrombotic signatures and are functionally pro-thrombotic, both at baseline and following ex vivo stimulation with SARS-CoV-2. Transcriptionally, COVID-19 monocytes are characterized by enrichment of pathways involved in hemostasis, immunothrombosis, platelet aggregation and other accessory pathways to platelet activation and clot formation. These results identify a potential mechanism by which monocyte dysfunction may contribute to COVID-19 pathology.

Lineage-specific rearrangement of chromatin loops and epigenomic features during adipocytes and osteoblasts commitment

Human mesenchymal stem cells (hMSCs) can be differentiated into adipocytes and osteoblasts. The processes are driven by the rewiring of chromatin architectures and transcriptomic/epigenomic changes. Here, we induced hMSCs to adipogenic and osteogenic differentiation, and performed 2 kb resolution Hi-C experiments for chromatin loops detection. We also generated matched RNA-seq, ChIP-seq and ATAC-seq data for integrative analysis. After comprehensively comparing adipogenesis and osteogenesis, we quantitatively identified lineage-specific loops and screened out lineage-specific enhancers and open chromatin. We reveal that lineage-specific loops can activate gene expression and facilitate cell commitment through combining enhancers and accessible chromatin in a lineage-specific manner. We finally proposed loop-mediated regulatory networks and identified the controlling factors for adipocytes and osteoblasts determination. Functional experiments validated the lineage-specific regulation networks towards IRS2 and RUNX2 that are associated with adipogenesis and osteogenesis, respectively. These results are expected to help better understand the chromatin conformation determinants of hMSCs fate commitment.

IL7 genetic variation and toxicity to immune checkpoint blockade in patients with melanoma

Treatment with immune checkpoint blockade (ICB) frequently triggers immune-related adverse events (irAEs), causing considerable morbidity. In 214 patients receiving ICB for melanoma, we observed increased severe irAE risk in minor allele carriers of rs16906115, intronic to IL7. We found that rs16906115 forms a B cell-specific expression quantitative trait locus (eQTL) to IL7 in patients. Patients carrying the risk allele demonstrate increased pre-treatment B cell IL7 expression, which independently associates with irAE risk, divergent immunoglobulin expression and more B cell receptor mutations. Consistent with the role of IL-7 in T cell development, risk allele carriers have distinct ICB-induced CD8+ T cell subset responses, skewing of T cell clonality and greater proportional repertoire occupancy by large clones. Finally, analysis of TCGA data suggests that risk allele carriers independently have improved melanoma survival. These observations highlight key roles for B cells and IL-7 in both ICB response and toxicity and clinical outcomes in melanoma.

An immune dysfunction score for stratification of patients with acute infection based on whole-blood gene expression

Dysregulated host responses to infection can lead to organ dysfunction and sepsis, causing millions of global deaths each year. To alleviate this burden, improved prognostication and biomarkers of response are urgently needed. We investigated the use of whole-blood transcriptomics for stratification of patients with severe infection by integrating data from 3149 samples from patients with sepsis due to community-acquired pneumonia or fecal peritonitis admitted to intensive care and healthy individuals into a gene expression reference map. We used this map to derive a quantitative sepsis response signature (SRSq) score reflective of immune dysfunction and predictive of clinical outcomes, which can be estimated using a 7- or 12-gene signature. Last, we built a machine learning framework, SepstratifieR, to deploy SRSq in adult and pediatric bacterial and viral sepsis, H1N1 influenza, and COVID-19, demonstrating clinically relevant stratification across diseases and revealing some of the physiological alterations linking immune dysregulation to mortality. Our method enables early identification of individuals with dysfunctional immune profiles, bringing us closer to precision medicine in infection.

Pneumolysin suppresses the initial macrophage pro-inflammatory response to Streptococcus pneumoniae

Published data for the Streptococcus pneumoniae virulence factor Pneumolysin (Ply) show contradictory effects on the host inflammatory response to infection. Ply has been shown to activate the inflammasome, but also can bind to MRC-1 resulting in suppression of dendritic cell inflammatory responses. We have used an in vitro infection model of human monocyte-derived macrophages (MDM), and a mouse model of pneumonia to clarify whether pro- or anti-inflammatory effects dominate the effects of Ply on the initial macrophage inflammatory response to S. pneumoniae, and the consequences during early lung infection. We found that infection with S. pneumoniae expressing Ply suppressed tumour necrosis factor (TNF) and interleukin-6 production by MDMs compared to cells infected with ply-deficient S. pneumoniae. This effect was independent of bacterial effects on cell death. Transcriptional analysis demonstrated S. pneumoniae expressing Ply caused a qualitatively similar but quantitatively lower MDM transcriptional response to S. pneumoniae compared to ply-deficient S. pneumoniae, with reduced expression of TNF and type I IFN inducible genes. Reduction of the MDM inflammatory response was prevented by inhibition of SOCS1. In the early lung infection mouse model, the TNF response to ply-deficient S. pneumoniae was enhanced and bacterial clearance increased compared to infection with wild-type S. pneumoniae. Overall, these data show Ply inhibits the initial macrophage inflammatory response to S. pneumoniae, probably mediated through SOCS1, and this was associated with improved immune evasion during early lung infection.

Immune dysfunction signatures predict outcomes and define checkpoint blockade-unresponsive microenvironments in acute myeloid leukemia

BackgroundImmune exhaustion and senescence are dominant dysfunctional states of effector T cells and major hurdles for the success of cancer immunotherapy. In the current study, we characterized how acute myeloid leukemia (AML) promotes the generation of senescent-like CD8+ T cells and whether they have prognostic relevance.METHODSWe analyzed NanoString, bulk RNA-Seq and single-cell RNA-Seq data from independent clinical cohorts comprising 1,896 patients treated with chemotherapy and/or immune checkpoint blockade (ICB).ResultsWe show that senescent-like bone marrow CD8+ T cells were impaired in killing autologous AML blasts and that their proportion negatively correlated with overall survival (OS). We defined what we believe to be new immune effector dysfunction (IED) signatures using 2 gene expression profiling platforms and reported that IED scores correlated with adverse-risk molecular lesions, stemness, and poor outcomes; these scores were a more powerful predictor of OS than 2017-ELN risk or leukemia stem cell (LSC17) scores. IED expression signatures also identified an ICB-unresponsive tumor microenvironment and predicted significantly shorter OS.ConclusionThe IED scores provided improved AML-risk stratification and could facilitate the delivery of personalized immunotherapies to patients who are most likely to benefit.TRIAL REGISTRATIONClinicalTrials.gov; NCT02845297.FUNDINGJohn and Lucille van Geest Foundation, Nottingham Trent University's Health & Wellbeing Strategic Research Theme, NIH/NCI P01CA225618, Genentech-imCORE ML40354, Qatar National Research Fund (NPRP8-2297-3-494).

Brain Catalog: a comprehensive resource for the genetic landscape of brain-related traits

A broad range of complex phenotypes are related to dysfunctions in brain (hereafter referred to as brain-related traits), including various mental and behavioral disorders and diseases of the nervous system. These traits in general share overlapping symptoms, pathogenesis, and genetic components. Here, we present Brain Catalog (https://ngdc.cncb.ac.cn/braincatalog), a comprehensive database aiming to delineate the genetic components of more than 500 GWAS summary statistics datasets for brain-related traits from multiple aspects. First, Brain Catalog provides results of candidate causal variants, causal genes, and functional tissues and cell types for each trait identified by multiple methods using comprehensive annotation datasets (58 QTL datasets spanning 6 types of QTLs). Second, Brain Catalog estimates the SNP-based heritability, the partitioning heritability based on functional annotations, and genetic correlations among traits. Finally, through bidirectional Mendelian randomization analyses, Brain Catalog presents inference of risk factors that are likely causal to each trait. In conclusion, Brain Catalog presents a one-stop shop for the genetic components of brain-related traits, potentially serving as a valuable resource for worldwide researchers to advance the understanding of how GWAS signals may contribute to the biological etiology of brain-related traits.

Transcriptomic Analysis of the Major Orphan Ichthyosis Subtypes Reveals Shared Immune and Barrier Signatures

Preliminary work suggested upregulation of inflammatory pathways in patients with common forms of ichthyosis. However, a comprehensive characterization of skin from various ichthyosis subtypes is unavailable, precluding the development of targeted treatments. Thus, we sought to characterize the immune and barrier profiles of common and subtype-specific skin transcriptomes in a large group of patients with ichthyosis. We performed a global RNA-sequencing analysis in 54 patients with ichthyosis (7 with Netherton syndrome, 13 with epidermolytic ichthyosis, 16 with lamellar ichthyosis, and 18 with congenital ichthyosiform erythroderma) and 40 healthy controls. Differentially expressed genes were defined on the basis of fold changes > 2 and false discovery rate < 0.05 criteria. We found robust and significant T helper (Th) 22/Th17 skewing in all subtypes (e.g., IL-17A/C/F, S100A7/8/9/12; P < 0.001) with modest changes in Th2 pathway, primarily in Netherton syndrome, and Th1 skewing in congenital ichthyosiform erythroderma. Across all subtypes (less evident in epidermolytic ichthyosis), lipid metabolism and barrier junction markers were downregulated (e.g., FA2H, CDH10/11/12/2; P < 0.05), whereas epidermal cornification and proliferation measures were upregulated (e.g., SPRR1A/1B/2C/2G, EREG; P < 0.05). Our findings suggest that the common ichthyosis variants share aberrations in Th17/Th22 and barrier function, with minimal Th2 modulation. This may help to elucidate the pathogeneses of these subtypes and inform the development of subtype-specific treatments.

Pericyte derived chemokines amplify neutrophil recruitment across the cerebrovascular endothelial barrier

Excessive neutrophil extravasation can drive immunopathology, exemplified in pyogenic meningitis caused by Streptococcus pneumoniae infection. Insufficient knowledge of the mechanisms that amplify neutrophil extravasation has limited innovation in therapeutic targeting of neutrophil mediated pathology. Attention has focussed on neutrophil interactions with endothelia, but data from mouse models also point to a role for the underlying pericyte layer, as well as perivascular macrophages, the only other cell type found within the perivascular space in the cerebral microvasculature. We tested the hypothesis that human brain vascular pericytes (HBVP) contribute to neutrophil extravasation in a transwell model of the cerebral post-capillary venule. We show that pericytes augment endothelial barrier formation. In response to inflammatory cues, they significantly enhance neutrophil transmigration across the endothelial barrier, without increasing the permeability to small molecules. In our model, neither pericytes nor endothelia responded directly to bacterial stimulation. Instead, we show that paracrine signalling by multiple cytokines from monocyte derived macrophages drives transcriptional upregulation of multiple neutrophil chemokines by pericytes. Pericyte mediated amplification of neutrophil transmigration was independent of transcriptional responses by endothelia, but could be mediated by direct chemokine translocation across the endothelial barrier. Our data support a model in which microbial sensing by perivascular macrophages generates an inflammatory cascade where pericytes serve to amplify production of neutrophil chemokines that are translocated across the endothelial barrier to act directly on circulating neutrophils. In view of the striking redundancy in inflammatory cytokines that stimulate pericytes and in the neutrophil chemokines they produce, we propose that the mechanism of chemokine translocation may offer the most effective therapeutic target to reduce neutrophil mediated pathology in pyogenic meningitis.

Grouping of UVCB substances with dose-response transcriptomics data from human cell-based assays

The application of in vitro biological assays as new approach methodologies (NAMs) to support grouping of UVCB (unknown or variable composition, complex reaction products, and biological materials) substances has recently been demonstrated. In addition to cell-based phenotyping as NAMs, in vitro transcriptomic profiling is used to gain deeper mechanistic understanding of biological responses to chemicals and to support grouping and read-across. However, the value of gene expression profiling for characterizing complex substances like UVCBs has not been explored. Using 141 petroleum substance extracts, we performed dose-response transcriptomic profiling in human induced pluripotent stem cell (iPSC)-derived hepatocytes, cardiomyocytes, neurons, and endothelial cells, as well as cell lines MCF7 and A375. The goal was to determine whether transcriptomic data can be used to group these UVCBs and to further characterize the molecular basis for in vitro biological responses. We found distinct transcriptional responses for petroleum substances by manufacturing class. Pathway enrichment informed interpretation of effects of substances and UVCB petroleum-class. Transcriptional activity was strongly correlated with concentration of polycyclic aromatic compounds (PAC), especially in iPSC-derived hepatocytes. Supervised analysis using transcriptomics, alone or in combination with bioactivity data collected on these same substances/cells, suggest that transcriptomics data provide useful mechanistic information, but only modest additional value for grouping. Overall, these results further demonstrate the value of NAMs for grouping of UVCBs, identify informative cell lines, and provide data that could be used for justifying selection of substances for further testing that may be required for registration.

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.

Natural Killer cells are key mediators of anti-tumour immunosurveillance and anti-viral immunity. Here, the authors map regulatory genetic variation in primary Natural Killer cells, providing new insights into their role in human health and disease.

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2-4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes-including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)-in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease.

Adrenal stress hormone regulation of hepatic homeostatic function after an acute ozone exposure in Wistar-Kyoto male rats

Ozone-induced lung injury and inflammation and pulmonary/hypothalamus gene expression changes are diminished in adrenalectomized (AD) rats. Acute ozone exposure induces metabolic alterations concomitant with increases in epinephrine and corticosterone. We hypothesized that adrenal hormones are responsible for observed hepatic ozone effects, and in AD rats, these changes would be diminished. 5-7 days after sham (SH) or AD surgeries, male Wistar-Kyoto rats were exposed to air or 0.8-ppm ozone for 4-hrs. Serum samples were analyzed for metabolites and liver for transcriptional changes immediately post-exposure. Ozone increased circulating triglycerides, cholesterol, free fatty-acids, and leptin in SH but not AD rats. Ozone-induced inhibition of glucose-mediated insulin release was absent in AD rats. Unlike diminution of ozone-induced hypothalamus and lung mRNA expression changes, AD in air-exposed rats (AD-air/SH-air) caused differential hepatic expression of ∼1000 genes. Likewise, ozone in AD rats caused differential expression of ∼1000 genes (AD-ozone/AD-air). Ozone-induced hepatic changes in SH rats reflected enrichment for pathways involving metabolic processes, including acetyl-CoA biosynthesis, TCA cycle, and sirtuins. Upstream predictor analysis identified similarity to responses produced by glucocorticoids and pathways involving forskolin. These changes were absent in AD rats exposed to ozone. However, ozone caused unique changes in AD liver mRNA reflecting activation of synaptogenesis, neurovascular coupling, neuroinflammation, and insulin signaling with inhibition of senescence pathways. In these rats, upstream predictor analysis identified numerous microRNAs involved in glucocorticoid insufficiency. These data demonstrate the critical role of adrenal stress hormones in ozone-induced hepatic homeostasis and necessitate further research elucidating their role in propagating environmentally driven diseases.

Association of FXI activity with thrombo-inflammation, extracellular matrix, lipid metabolism and apoptosis in venous thrombosis

Animal experiments and early phase human trials suggest that inhibition of factor XIa (FXIa) safely prevents venous thromboembolism (VTE), and specific murine models of sepsis have shown potential efficacy in alleviating cytokine storm. These latter findings support the role of FXI beyond coagulation. Here, we combine targeted proteomics, machine learning and bioinformatics, to discover associations between FXI activity (FXI:C) and the plasma protein profile of patients with VTE. FXI:C was measured with a modified activated partial prothrombin time (APTT) clotting time assay. Proximity extension assay-based protein profiling was performed on plasma collected from subjects from the Genotyping and Molecular Phenotyping of Venous Thromboembolism (GMP-VTE) Project, collected during an acute VTE event (n = 549) and 12-months after (n = 187). Among 444 proteins investigated, N = 21 and N = 66 were associated with FXI:C during the acute VTE event and at 12 months follow-up, respectively. Seven proteins were identified as FXI:C-associated at both time points. These FXI-related proteins were enriched in immune pathways related to causes of thrombo-inflammation, extracellular matrix interaction, lipid metabolism, and apoptosis. The results of this study offer important new avenues for future research into the multiple properties of FXI, which are of high clinical interest given the current development of FXI inhibitors.

Genome-wide association analysis and replication in 810,625 individuals with varicose veins

Varicose veins affect one-third of Western society, with a significant subset of patients developing venous ulceration, costing $14.9 billion annually in the USA. Current management consists of either compression stockings, or surgical ablation for more advanced disease. Most varicose veins patients report a positive family history, and heritability is ~17%. We describe the largest two-stage genome-wide association study of varicose veins in 401,656 individuals from UK Biobank, and replication in 408,969 individuals from 23andMe (total 135,514 cases and 675,111 controls). Forty-nine signals at 46 susceptibility loci were discovered. We map 237 genes to these loci, several of which are biologically plausible and tractable to therapeutic targeting. Pathway analysis identified enrichment in extracellular matrix biology, inflammation, (lymph)angiogenesis, vascular smooth muscle cell migration, and apoptosis. Using a polygenic risk score (PRS) derived in an independent cohort, we demonstrate its predictive utility and correlation with varicose veins surgery.

PiER: web-based facilities tailored for genetic target prioritisation harnessing human disease genetics, functional genomics and protein interactions

Integrative prioritisation promotes translational use of disease genetic findings in target discovery. I report ‘PiER’ (http://www.genetictargets.com/PiER), web-based facilities that support ab initio and real-time genetic target prioritisation through integrative use of human disease genetics, functional genomics and protein interactions. By design, the PiER features two facilities: elementary and combinatory. The elementary facility is designed to perform specific tasks, including three online tools: eV2CG, utilising functional genomics to link disease-associated variants (particularly located at the non-coding genome) to core genes likely responsible for genetic associations in disease; eCG2PG, using knowledge of protein interactions to ‘network’ core genes and additional peripheral genes, producing a ranked list of core and peripheral genes; and eCrosstalk, exploiting the information of pathway-derived interactions to identify highly-ranked genes mediating crosstalk between molecular pathways. Each of elementary tasks giving results is sequentially piped to the next one. By chaining together elementary tasks, the combinatory facility automates genetics-led and network-based integrative prioritisation for genetic targets at the gene level (cTGene) and at the crosstalk level (cTCrosstalk). Together with a tutorial-like booklet describing instructions on how to use, the PiER facilities meet multi-tasking needs to accelerate computational translational medicine that leverages human disease genetics and genomics for early-stage target discovery and drug repurposing.

Genomic Evidence Supports the Recognition of Endometriosis as an Inflammatory Systemic Disease and Reveals Disease-Specific Therapeutic Potentials of Targeting Neutrophil Degranulation

Background

Endometriosis, classically viewed as a localized disease, is increasingly recognized as a systemic disease with multi-organ effects. This disease is highlighted by systemic inflammation in affected organs and by high comorbidity with immune-mediated diseases.

Results

We provide genomic evidence to support the recognition of endometriosis as an inflammatory systemic disease. This was achieved through our genomics-led target prioritization, called ‘END’, that leverages the value of multi-layered genomic datasets (including genome-wide associations in disease, regulatory genomics, and protein interactome). Our prioritization recovered existing proof-of-concept therapeutic targeting in endometriosis and outperformed competing prioritization approaches (Open Targets and Naïve prioritization). Target genes at the leading prioritization revealed molecular hallmarks (and possibly the cellular basis as well) that are consistent with systemic disease manifestations. Pathway crosstalk-based attack analysis identified the critical gene AKT1. In the context of this gene, we further identified genes that are already targeted by licensed medications in other diseases, such as ESR1. Such analysis was supported by current interests targeting the PI3K/AKT/mTOR pathway in endometriosis and by the fact that therapeutic agents targeting ESR1 are now under active clinical trials in disease. The construction of cross-disease prioritization map enabled the identification of shared and distinct targets between endometriosis and immune-mediated diseases. Shared target genes identified opportunities for repurposing existing immunomodulators, particularly disease-modifying anti-rheumatic drugs (such as TNF, IL6 and IL6R blockades, and JAK inhibitors). Genes highly prioritized only in endometriosis revealed disease-specific therapeutic potentials of targeting neutrophil degranulation – the exocytosis that can facilitate metastasis-like spread to distant organs causing inflammatory-like microenvironments.

Conclusion

Improved target prioritization, along with an atlas of in silico predicted targets and repurposed drugs (available at https://23verse.github.io/end), provides genomic insights into endometriosis, reveals disease-specific therapeutic potentials, and expands the existing theories on the origin of disease.

Rapid synchronous type 1 IFN and virus-specific T cell responses characterize first wave non-severe SARS-CoV-2 infections

Effective control of SARS-CoV-2 infection on primary exposure may reveal correlates of protective immunity to future variants, but we lack insights into immune responses before or at the time virus is first detected. We use blood transcriptomics, multiparameter flow cytometry, and T cell receptor (TCR) sequencing spanning the time of incident non-severe infection in unvaccinated virus-naive individuals to identify rapid type 1 interferon (IFN) responses common to other acute respiratory viruses and cell proliferation responses that discriminate SARS-CoV-2 from other viruses. These peak by the time the virus is first detected and sometimes precede virus detection. Cell proliferation is most evident in CD8 T cells and associated with specific expansion of SARS-CoV-2-reactive TCRs, in contrast to virus-specific antibodies, which lag by 1-2 weeks. Our data support a protective role for early type 1 IFN and CD8 T cell responses, with implications for development of universal T cell vaccines.

A blood atlas of COVID-19 defines hallmarks of disease severity and specificity

Treatment of severe COVID-19 is currently limited by clinical heterogeneity and incomplete description of specific immune biomarkers. We present here a comprehensive multi-omic blood atlas for patients with varying COVID-19 severity in an integrated comparison with influenza and sepsis patients versus healthy volunteers. We identify immune signatures and correlates of host response. Hallmarks of disease severity involved cells, their inflammatory mediators and networks, including progenitor cells and specific myeloid and lymphocyte subsets, features of the immune repertoire, acute phase response, metabolism, and coagulation. Persisting immune activation involving AP-1/p38MAPK was a specific feature of COVID-19. The plasma proteome enabled sub-phenotyping into patient clusters, predictive of severity and outcome. Systems-based integrative analyses including tensor and matrix decomposition of all modalities revealed feature groupings linked with severity and specificity compared to influenza and sepsis. Our approach and blood atlas will support future drug development, clinical trial design, and personalized medicine approaches for COVID-19.

Metagenomics and chemotherapy-induced nausea: A roadmap for future research

Uncontrolled chemotherapy-induced nausea and vomiting can reduce patients' quality of life and may result in premature discontinuation of chemotherapy. Although nausea and vomiting are commonly grouped together, research has shown that antiemetics are clinically effective against chemotherapy-induced vomiting (CIV) but less so against chemotherapy-induced nausea (CIN). Nausea remains a problem for up to 68% of patients who are prescribed guideline-consistent antiemetics. Despite the high prevalence of CIN, relatively little is known regarding its etiology independent of CIV. This review summarizes a metagenomics approach to the study and treatment of CIN with the goal of encouraging future research. Metagenomics focuses on genetic risk factors and encompasses both human (ie, host) and gut microbial genetic variation. Little work to date has focused on metagenomics as a putative biological mechanism of CIN. Metagenomics has the potential to be a powerful tool in advancing scientific understanding of CIN by identifying new biological pathways and intervention targets. The investigation of metagenomics in the context of well-established demographic, clinical, and patient-reported risk factors may help to identify patients at risk and facilitate the prevention and management of CIN.

echolocatoR: an automated end-to-end statistical and functional genomic fine-mapping pipeline

SUMMARY

echolocatoR integrates a diverse suite of statistical and functional fine-mapping tools to identify, test enrichment in, and visualize high-confidence causal consensus variants in any phenotype. It requires minimal input from users (a summary statistics file), can be run in a single R function, and provides extensive access to relevant datasets (e.g. reference linkage disequilibrium panels, quantitative trait loci, genome-wide annotations, cell-type-specific epigenomics), thereby enabling rapid, robust and scalable end-to-end fine-mapping investigations.

AVAILABILITY AND IMPLEMENTATION

echolocatoR is an open-source R package available through GitHub under the GNU General Public License (Version 3) license: https://github.com/RajLabMSSM/echolocatoR.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.